2015 international conference on machine learning and ...toc.proceedings.com/28487webtoc.pdf ·...

12
IEEE Catalog Number: ISBN: CFP15523-POD 978-1-4673-7222-0 2015 International Conference on Machine Learning and Cybernetics (ICMLC 2015) Guangzhou, China 12-15 July 2015 Volume 1 Pages 1-461 1/2

Upload: phamdung

Post on 18-Mar-2018

218 views

Category:

Documents


1 download

TRANSCRIPT

Page 1: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

IEEE Catalog Number: ISBN:

CFP15523-POD 978-1-4673-7222-0

2015 International Conference on Machine Learning and Cybernetics (ICMLC 2015)

Guangzhou, China 12-15 July 2015

Volume 1 Pages 1-461

1/2

Page 2: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

     

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, Guangzhou, 12-15 July, 2015 

Contents DISTANCE OF SPECIAL MULTI-DIMENSIONAL FUZZY NUMBER SPACE AND ITS APPLICATION

GUIXIANG WANG, YUN LI ................................................................................................................................................................. 1

PREDICTION OF PROTEIN STRUCTURAL CLASSES BY DECREASING NEAREST NEIGHBOR ERROR RATE

SU-PING XU, XI-BEI YANG, XIAO-NING SONG, HUA-LONG YU ................................................................................................. 7

PARAMETER LEARNING FOR ANT COLONY OPTIMIZATION TO MINIMAL TIME COST REDUCTION

JI DONG, HUAN YANG, ZHI-HENG ZHANG, FAN MIN ................................................................................................................. 14

PARAMETERIZED REDUCTION OF COVERING DECISION SYSTEMS

DE-LIANG MA, DE-GANG CHEN, XIAO-XIA ZHANG .................................................................................................................. 20

GRAPH K-MEANS WITH LOST CLUSTER APPROACH FOR NONLINEAR MANIFOLD CLUSTERING

QUOC-THANG LY, PHUOC-HUNG TRUONG, HOANG-THAI LE ................................................................................................... 25

SYSTEM IDENTIFICATION USING DIFFERENTIAL EVOLUTION WITH MEAN-BEST MUTATION

MING-FENG YEH, HUNG-CHING LU, MIN-SHYANG LEU, YI-FAN LEE ...................................................................................... 31

BASED ON MULTI-DIRECTIONAL MULTI-SCALE WEIGHTED MORPHOLOGY FOD IMAGES ENHANCE ALGORITHM

GUO YANYING, LIU ZHIGANG, JIANG LIHUI ............................................................................................................................... 36

IMPROVED VARIABLE UNIVERSE FUZZY PID APPLICATION IN BEER FERMENTATION PROCESS

XUE-SONG WANG, CHAOYING LIU, ZHEYING SONG, BINGBING WU ................................................................................... 40

IDENTIFICATION OF FUNCTION MODULES IN PROTEIN-PROTEIN INTERACTION NETWORKS BY MODULARITY

OPTIMIZATION METHOD

JUN FENG, NING-NING JIA, ZHAO-HUI QI, XIAO-FEN ZHANG ................................................................................................. 47

FREEWAY RAMP METERING BASED ON GENETIC ALGORITHM OPTIMIZATION

HAI LONG, SHENG-SHENG CAI, XIN-RONG LIANG, QI LU ....................................................................................................... 52

MULTIGRANULATION INFORMATION FUSION: A DEMPSTER-SHAFEREVIDENCE THEORY BASED CLUSTERING

ENSEMBLE METHOD

FEI-JIANG LI, YU-HUA QIAN, JIE-TING WANG, JI-YE LIANG .................................................................................................... 58

RESEARCH ON KEY TECHNOLOGIES OF GEOGRAPHIC INFORMATION PUBLIC SERVICE PLATFORM BASED ON

GAOFEN-1

XIAO-HONG WANG, JIN-JIN GAO, HUI-CONG WU, CHEN-HUA JIA .......................................................................................... 64

STEALTHY BEHAVIOR SIMULATIONS BASED ON COGNITIVE DATA

TAEYEONG CHOI, HYEON-SUK NA ................................................................................................................................................ 68

OPTIMAL FEATURE SUBSET WITH POSITIVE REGION CONSTRAINT

JUN-XIA NIU, HONG ZHAO, WILLIAM ZHU .................................................................................................................................. 75

COST-SENSITIVE DECISION TREE WITH PROBABILISTIC PRUNINGMECHANISM

HONG ZHAO, XIANG-JU LI, ZI-LONG XU, WILLIAM ZHU ......................................................................................................... 81

A NEW PARTICLE SWARM ALGORITHM BY MODIFYING ITS TOPOLOGY STRUCTURE

KAI-SHI XU, YANG YI ........................................................................................................................................................................ 88

Page 3: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

     

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, Guangzhou, 12-15 July, 2015 

A MATROIDAL STRUCTURE FOR FORMAL CONTEXT AND ITSAPPLICATIONS ON EPIDEMIOLOGICAL STUDY

DUI-XIA MA, WILLIAM ZHU ............................................................................................................................................................ 93

INDEX CREATION AND OPTIMIZE QUERY PERFORMANCE IN THE TRANSPORT SECTOR

LE-LE REN, LING-MIN HE ................................................................................................................................................................ 99

MORPHOLOGICAL COMPONENT ANALYSIS AND LEAST SQUARES SUPPORT VECTOR MACHINE FOR IMAGE

SUPER-RESOLUTION

YIH-LON LIN, YU-MIN CHIANG, YI-LING TSAI .......................................................................................................................... 104

RESEARCH ON SPEED AND TENSION MULTIVARIABLE SYSTEM OF REVERSIBLE COLD STRIP MILL BASED ON ILQ

THEORY

GANG ZHENG, XIAO-LI CHAO, ZHE YANG, FU-CAI QIAN ....................................................................................................... 110

3VL-MLP: A WAY FOR REALIZING INTERPRETABLE AWARE SYSTEMS

QIANGFU ZHAO ............................................................................................................................................................................... 116

SELECTION OF INITIAL PARAMETERS OF K-MEANS CLUSTERING ALGORITHM FOR MRI BRAIN IMAGE

SEGMENTATION

JIAN-WEI LIU, LEI GUO .................................................................................................................................................................. 123

CLASSIFICATION ON TIANGONG-1 HYPERSPECTRAL REMOTE SENSING IMAGE VIA CONTEXTUAL SPARSE CODING

QI LV, YONG DOU, XIN NIU, JIAQING XU, JINBO XU ................................................................................................................ 128

CLASSIFYING GENE DATA WITH REGULARIZED ENSEMBLE TREES

THANH-TUNG NGUYEN, HUONG NGUYEN, YINXU WU, MARK JUNJIE LI ......................................................................... 134

PARITY SYMMETRICAL SRC ALGORITHM FOR FACE RECOGNITION

XIAONING SONG, XIBEI YANG ..................................................................................................................................................... 140

TOWARDS LEARNING SEGMENTED TEMPORAL SEQUENCES: A DECISION TREE APPROACH

QIANQIAN SHI, YING ZHAO, MINGLIANG LIU .......................................................................................................................... 145

MINING GOLD IN SENIOR EXECUTIVES’ POCKETS: AN ONLINE AUTOMATICALLY TRADING STRATEGY

CHAO MA, XUN LIANG ................................................................................................................................................................... 151

INCREMENTAL UPDATING FUZZY ROUGH APPROXIMATIONS FOR DYNAMIC HYBRID DATA UNDER THE

VARIATION OF ATTRIBUTE VALUES

ANPING ZENG, TIANRUI LI, CHUAN LUO, JIE HU ..................................................................................................................... 157

A CLOUD TESTING PLATFORM AND ITS METHODS BASED ON ESSENTIAL CLOUD CHARACTERISTICS

CHI-JUNG LI, HEH-JIANN SHIH ..................................................................................................................................................... 163

INFORMATION FUSION IN MULTI-SOURCE FUZZY INFORMATION SYSTEM WITH SAME STRUCTURE

JIANHANG YU, WEIHUA XU .......................................................................................................................................................... 170

A SIMPLIFIED EDGE-COUNTING METHOD FOR MEASURING SEMANTIC SIMILARITY OF CONCEPTS

JIAN-BO GAO, BAO-WEN ZHANG, XIAO-HUA CHEN ............................................................................................................... 176

INFORMATION GRANULES IN MULTI-SCALE ORDERED INFORMATION SYSTEMS

WEI-ZHI WU, SHEN-MING GU, XIA WANG .................................................................................................................................. 182

BOUNDARY REGION-BASED ROUGH SETS

ZHOU-MING MA, JU-SHENG MI .................................................................................................................................................... 188

Page 4: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

     

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, Guangzhou, 12-15 July, 2015 

SELECTIVE ENSEMBLE LEARNING WITH PARALLEL OPTIMIZATION AND HIERARCHICAL SELECTION

JIA-SHENG GUO, JIAN-CANG ZENG, JIN-XIU CHEN, QUAN ZOU .......................................................................................... 194

A NEW POWER GENERATION CALCULATION METHOD FOR VERTICAL AXIS WIND TURBINE CONTROL

ZHENG LI, PEI-FENG GAO, TIAN-TIAN SUN ............................................................................................................................... 200

FREE AND OPEN SOURCE INTRUSION DETECTION SYSTEMS: A STUDY

SREENIVAS SREMATH TIRUMALA, HIRA SATHU, ABDOLHOSSEIN SARRAFZADEH ........................................................ 205

ENSEMBLE LEARNING METHODS FOR DECISION MAKING: STATUS AND FUTURE PROSPECTS

SHAHID ALI, SREENIVAS SREMATH TIRUMALA, ABDOLHOSSEIN SARRAFZADEH ......................................................... 211

TEXTURE FEATURE EXTRACTION OF STEEL STRIP SURFACE DEFECT BASED ON GRAY LEVEL CO-OCCURRENCE

MATRIX

YING-JUN GUO, ZI-JUN SUN, HE-XU SUN, XUE-LING SONG .................................................................................................. 217

A SPARSE FEATURE REPRESENTATION FOR GENETIC DATA ANALYSIS

HUA-HAO LIU, PEI-JIE HUANG, PEI-JIE HUANG, PI-YUAN LIN, WEN-HU LIN, PEI-HENG QI, CHONG-HUA SONG ...... 222

A FEATURE GENERATION FRAMEWORK FOR GOOGLE TRACE ANALYSIS

ZI-WEI FAN, PEI-JIE HUANG, PEI-SEN HUANG, LIN-XIAO CHEN, YU-QING XIAO, MING-XIANG HUO, YU LIANG .... 229

THE FARTHEST NEIGHBOR QUERIES BASED ON R-TREES

RUN-TAO LIU, CHENG CHANG, ZHI-QIANG MAN, ZHONG WANG ........................................................................................ 235

MULTIPLE INDEXES COMBINATION WEIGHTING FOR DORSAL HAND VEIN IMAGE QUALITY ASSESSMENT

YI-DING WANG, CHEN-YAN YANG, QIANG-YU DUAN ............................................................................................................. 239

STATIC OUTPUT FEEDBACK CONTROL FOR H ∞ STABILITY AND CONSENSUS OF NONLINEAR COMPLEX

DYNAMICAL NETWORKS

AO DUN, LILI XIA, DI LIANG, YU ZHAO ..................................................................................................................................... 246

COST-SENSITIVE REGRESSION-BASED RECOMMENDER SYSTEM

HENG-RU ZHANG, FAN MIN, DOMINIK SLEZAK, BING SHI .................................................................................................... 253

FINE-GRAINED ACRONYM EXPANSION IDENTIFICATION USINGLATENT-STATE NEURAL STRUCTURED

PREDICTION MODEL

JIE LIU, CAIHUA LIU, QINGHUA HU, YALOU HUANG .............................................................................................................. 259

A NEW TYPE OF GENERALIZED ONE-SIDED CONCEPT LATTICES AND ITS KNOWLEDGE REDUCTION

MING-WEN SHAO, KE-WEN LI ...................................................................................................................................................... 265

SENTIMENT ANALYSIS OF MIXED LANGUAGE EMPLOYING HINDI-ENGLISH CODE SWITCHING

PROF. DINKAR SITARAM, MS. SAVITHA MURTHY, DEBRAJ RAY, DEVANSH SHARMA, KASHYAP DHAR .................... 271

RADIUS-MARGIN BASED SUPPORT VECTOR MACHINE WITH LOGDET REGULARIZATION

YUAN-YUAN ZHU, XIAO-HE WU, JUN XU, DAVID ZHANG, WANG-MENG ZUO ................................................................. 277

GENE REGULATORY EFFECTS INFERENCE FOR CELL FATE DETERMINATION BASED ON SINGLE-CELL

RESOLUTION DATA

XIAO-TAI HUANG, LEANNE L. H. CHAN, ZHONG-YING ZHAO, HONG YAN ........................................................................ 283

COGNITIVE CONCEPT LEARNING VIA GRANULAR COMPUTING FOR BIG DATA

JINHAI LI, CHENCHEN HUANG, WEIHUA XU, YUHUA QIAN, WENQI LIU ........................................................................... 289

Page 5: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

     

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, Guangzhou, 12-15 July, 2015 

RESEARCH ON THE IMAGE COMPLEXITY BASED ON NEURAL NETWORK

YAN-QIN CHEN, JIN DUAN, YONG ZHU, XIAO-FEI QIAN, BO XIAO ...................................................................................... 295

FINDING DOMAIN-SPECIFIC TERMS FROM SEARCH ENGINE’S QUERY LOGS

WEIJIAN NI, TONG LIU, QINGTIAN ZENG ................................................................................................................................... 301

GENERAL AIRCRAFT 4D FLIGHT TRAJECTORY PREDICTION METHOD BASED ON DATA FUSION

ZHENG LI, SHUANG-HONG LI, XUE-LI WU ................................................................................................................................ 309

PARALLEL KNOWLEDGE ACQUISITION ALGORITHM FOR BIG DATA USING MAPREDUCE

JIN QIAN, MIN XIA, PING LV .......................................................................................................................................................... 316

AN INTEGRATED FRAMEWORK FOR AERIAL IMAGE RESTORATION

NGAIMING KWOK, HAIYAN SHI ................................................................................................................................................... 322

TYPICAL HESITANT FUZZY ROUGH SETS

SHU-YUN YANG, HONG-YING ZHANG ........................................................................................................................................ 328

PEOPLE GATHERING RECOGNITION BASED ON DYNAMIC TEXTURE DETECTION

WEI-LIEH HSU, TI-HUNG CHEN .................................................................................................................................................... 334

REVERSIBLE DATA HIDING FOR VQ INDICES USING XOR OPERATOR AND SOC CODES

CHIN-CHEN CHANG, YING-HSUAN HUANG, WEI-CHI CHANG .............................................................................................. 340

A NEW METHOD FOR FUZZY INTERPOLATIVE REASONING BASED ON RANKING VALUES OF POLYGONAL FUZZY

SETS AND AUTOMATICALLY GENERATED WEIGHTS OF FUZZY RULES

SHOU-HSIUNG CHENG, SHYI-MING CHEN, CHIA-LING CHEN ............................................................................................... 346

ADAPTIVE FUZZY INTERPOLATION FOR SPARSE FUZZY RULE-BASED SYSTEMS

SHOU-HSIUNG CHENG, SHYI-MING CHEN, CHIA-LING CHEN ............................................................................................... 352

A NEW METHOD FOR FUZZY MULTIATTRIBUTE GROUP DECISION MAKING BASED ON INTUITIONISTIC FUZZY

SETS AND THE EVIDENTIAL REASONING METHODOLOGY

SHYI-MING CHEN, SHOU-HSIUNG CHENG, CHU-HAN CHIOU ............................................................................................... 359

A NEW METHOD FOR WEIGHTED FUZZY INTERPOLATIVE REASONING BASED ON PIECEWISE FUZZY ENTROPIES

OF FUZZY SETS

SHYI-MING CHEN, E-JIN CHEN ..................................................................................................................................................... 365

RANKING TYPE 2 FUZZY SETS BY PARAMETRIC EMBEDDED REPRESENTATION

KUO-PING CHIAO ............................................................................................................................................................................ 371

HYBRID ENSEMBLE LEARNING APPROACH FOR GENERATION OF CLASSIFICATION RULES

HAN LIU, ALEXANDER GEGOV, MIHAELA COCEA ................................................................................................................... 377

PIECEWISE LINEAR HIGH-ORDER HIDDEN MARKOV MODELS AND APPLICATIONS TO SPEECH RECOGNITION

LEE-MIN LEE .................................................................................................................................................................................... 383

INTUITIVE MUSCLE-GESTURE BASED ROBOT NAVIGATION CONTROL USING WEARABLE GESTURE ARMBAND

GUAN-CHUN LUH, HENG-AN LIN, YI-HSIANG MA, CHIEN-JUNG YEN ................................................................................ 389

A PITCH-CONTOUR GENERATION METHOD COMBINING ANN, GLOBAL VARIANCE, AND REAL-CONTOUR

SELECTION

HUNG-YAN GU, KAI-WEI JIANG ................................................................................................................................................... 396

Page 6: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

     

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, Guangzhou, 12-15 July, 2015 

OBSTACLE DETECTION AND AVOIDING VIA CASCADE CLASSIFIER ON WHEELED MOBILE ROBOT

CHUNG-JUNG LEE, TENG-HUI TSENG, BO-JHEN HUANG, JUN-WEI HSIEH, CHUN-MING TSAI ...................................... 403

FAST HAND DETECTION AND GESTURE RECOGNITION

YUH-RAU WANG, JIA-LIANG SYU, HSIN-TING LI, LING YANG .............................................................................................. 408

IMPLEMENTING GREY RELATION FOR SURFACE ROUGNESS ANALYSIS IN MILLING OPERATIONS

POTSANG B. HUANG, HUANG-JIE ZHANG, JAMES C. CHEN, PO-YI LU ................................................................................ 414

QUALITY-EFFICIENT UNIVERSAL DEMOSAICING FOR ARBITRARY COLOR FILTER ARRAY VIDEOS USING SPATIAL

AND TEMPORAL CORRELATIONS

KUO-LIANG CHUNG, CHIEN-HSIUNG LIN, WEI-CHEN JIAN ................................................................................................... 420

A NEW METHOD FOR MULTIPLE ATTRIBUTE DECISION MAKING BASED ON INTUITIONISTIC FUZZY GEOMETRIC

AVERAGING OPERATORS

SHYI-MING CHEN, CHIA-HAO CHANG ........................................................................................................................................ 426

USING INTELLIGENT AGENT TO BUILD TODDLER MONITORING SYSTEM

TONG ZHENG, JUN-CHENG WANG, MENG-JYUN WENG, YUN-MENG LIANG, YUH-TZONG LIU, CHUN-JUNG LIN .... 433

HEWIN: HIGH EXPECTED WEIGHTED ITEMSET MINING IN UNCERTAIN DATABASES

JERRY CHUN-WEI LIN, WENSHENG GAN, TZUNG-PEI HONG, VINCENT S. TSENG ........................................................... 439

ADAPTIVE DENSITY-BASED SPATIAL CLUSTERING OF APPLICATIONS WITH NOISE (DBSCAN) ACCORDING TO DATA

WEI-TUNG WANG, YI-LEH WU, CHENG-YUAN TANG, MAW-KAE HOR ................................................................................ 445

AN EXPERIMENTAL STUDY ON INDOOR AIR QUALITY AND THE ENERGY CONSUMPTION IN A BUILDING BY FUZZY

CONTROL

WANG-KUN CHEN, CHIN-TE WANG, MING-WEI LIN ................................................................................................................ 452

A HIERARCHICAL RELIABILITY-DRIVEN SCHEDULING FOR CLOUD VIDEO TRANSCODING

CHUNG-YI WU, HAN-YEN YU, JING-CHEN HUANG, JIANN-JONE CHEN .............................................................................. 456

Page 7: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

IEEE Catalog Number: ISBN:

CFP15523-POD 978-1-4673-7222-0

2015 International Conference on Machine Learning and Cybernetics (ICMLC 2015)

Guangzhou, China 12-15 July 2015

Volume 2 Pages 462-920

2/2

Page 8: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

����� ������������� ��������� ��� �������������������������������������� �������������������� ����������!"#$%#$&��'(')*+,+�-.�/+,(0�.1'!2')�3,45(+,-(�'(3�65!2-1�7/'(2,8'2,-(�,(�!9,1���:;<=>;�?@A@��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CDE�!-4F15G5(+,65�25+2�-.�G,0G�3*('4,!�1'(05�,4'05+���H>A<IA;J�K>@��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CDD�'�(5L�.157/5(2�,254�+52�4,(,(0�')0-1,2G4�9'+53�-(�,(2516')�,(251+5!2,-(���KM;J@N<O>MP�Q:;A:�MR:IA��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CST�'(�5..5!2,65�'(3�5..,!,5(2�01,3U9'+53�3'2'�!)/+251,(0�')0-1,2G4�/+,(0�,(2/,2,65�(5,0G9-1�15)'2,-(+G,F�.-1�3'2'�4,(,(0���V@>;J<W:�R?:AP�?@>;J<V@A:;J�@M:;J��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CSX�'�+2/3*�-.�G'(3�05+2/15�15!-0(,2,-(�L,2G�L,15)5++�!G'((5)�4-35),(0�9*�/+,(0�L5'1'9)5�356,!5+���KM;J<W:�@M:;JP�@M:<YMA�K:;JP�R:;<@?M�R:;��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CXC�!-)-/1U54-2,-(�'++-!,'2,-(�+2/3*�-(�'9+21'!2�'12�F',(2,(0���VAZ�W:=AO:@�@A[:\MOO:@P�:O:;�H>><V@M;J�OA>HP�YM;�YN��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CXX�9'(3L,32G�F51.-14'(!5�'(')*+,+�L,2G�'�6'1,'2,-(�-.�L59F'05�+,85+���V@M;J<]A;J�V@>;P�JM:;<Y@N;J�OA;P�K>;<@?A;J�OA;P�@M:A<]A;J�?N;J��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�CC�0.5'2/15�+5)5!2,-(�'(3�15!-0(,2,-(�-.�5)5!21-5(!5FG')-01'4�+,0(')+_�'(�5 21545�)5'1(,(0�4'!G,(5�'(3�05(52,!�')0-1,2G4U9'+53�'FF1-'!G���aA;�OA;P�YA:<[N�@M:;JP�YA:;�=@N;JP�?A<\:�OA;P�KM;�bM>��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�C �9,!)/+251,(0�'(')*+,+�-.�05(5�5 F15++,-(�3'2'�/+,(0�4/)2,U-9c5!2,65�56-)/2,-('1*�')0-1,2G4+���I:dK:I�JNOV@A;P�?>K>\�@:?@>I�\:Q:d]:;:@P�:O:;�H>><V@M;J�OA>H��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�efe�./+,-(�9'+53�'FF1-'!G�2-�3,+!-651,(0�+-!,')�!,1!)5+�,(�50-�(52L-1g+���:B�Z:I:OP�IB�IB�OMRW>�>O:@AP�[dMV>�]NN;P�IB�:?@d:WMO�:IA;�BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eTT�+5(2,45(2�!)'++,.,!'2,-(�/+,(0�2.U,3.�.5'2/15+�'(3�5 25(353�+F'!5�.-15+2�5(+549)5���;A>aA;J�V:NP�YA;JYA;J�V:NP�@:AOA�OMP�[A;J�OA��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eED�'�!-))'9-1'2,65�.,)251,(0�')0-1,2G4�9'+53�-(�9,!)/+251,(0���H>AbA;J�=@NMP�J>J>�=@:;JP�bA:NdN;J�=@:NP�I>A@:;J�OAP�bA:N@MA�@MP�KM;�bM>��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�ehh�'�15')U2,45�F'1'))5)�!-49,('2,-(�+5045(2'2,-(�452G-3�.-1�')/4,(/4�+/1.'!5�35.5!2�,4'05+���bAM<aA;�@M:;JP�bA;<[A;�OMNP�d>;<=@N;J�H:;J��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eCC�2G5�F-L51�+2/3*�'9-/2�2G155�+2'2,+2,!+�-.�'),0(45(2U.155�!-4F'1,+-(�9'+53�-(�'2U1,!G�4-35)���bM><I>A�OAMP�dMA<[A;�@>P�[N<\N;J�OAMP�bA:;J=:;JP�KM<bA:�=@:;JP�H>;<K:N�OA:;J��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eef�9/,)3,(0�6'1,'9)5�+5)5!2,-(�5(+549)5+�.-1�),(5'1�15015++,-(�4-35)+�9*�'33,(0�(-,+5���JM:;<H>A�H:;JP�V@M;<bA:�=@:;J��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eeC�35+,0(�-.�./88*�(5/1')�(52L-1g�!-(21-)�.-1�+,(0)5U+2'05�9--+2�,(651251���dN;J<YN;J�H:AP�K:N<Z:A�OAM��BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB�eDf�

Page 9: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

����� ������������� ��������� ��� �������������������������������������� �������������������� ����������!"#$%&'�!"(%()*!�+#("$�*&�%,#'"�-!*."((%&'���/012345612�75618�96123/:0�;:12�<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=>>�#�&"?�#$#-)%@"�ABCCD�&"B!#E�A*!."�.*&)!*EE"!�A*!�!*+*)(�,#&%-BE#)*!�%&)"!#.)%&'�?%)F�"&@%!*&,"&)(���GH123/0�95:18�75I1235012�J668�75I53KI1�JI1��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=LM�F.!AN$!%@"&�+"#,A*!,%&'�A*!�!"@"!+"!#&)�(-"".F�!".*'&%)%*&���;6I3O/12�5H12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=LP�+B%E$%&'�#�-E#)A*!,�A*!�,*&%)*!%&'�?"#)F"!�.*&$%)%*&(�?%)F�,"#(B!","&)(�.*,-#!%(*&���75613/I�JI08�45I535:0�Q:12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=PM�E*?N.*()�A#.%#E�"R-!"((%*&�*&�,*+%E"�-E#)A*!,���75:12375017508�S0:13/0�75618�9013;6I�54I65��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=P>�#B)*,#)%.�$")".)%*&�#&$�!",*@"�*A�.*E*!�.*,,"&)(�A!*,+**T�%,#'"(���20:12350I�S:I8�/03UH�/0:18�9I12�G5:128�G5I350:�7561��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=VW�,BE)%N-E#&�A*!�*-)%,#E�,%R�*A�)!#@"E�!*B)"(���X03Q612�45:12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=V=�%,#'"�("',"&)#)%*&�?%)F�)"R)B!"�.EB()"!%&'�+#("$�Y("'���9I12�G5:128�/H123;6I�2:H8�456123;6I�Q6128�G5I350:�75618�/03UH�/0:1��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�=VV�#B)*,#)%.�.F%&"("�$%#E*'�#.)(�!".*'&%)%*&�?%)F�,BE)%-E"�T"!&"E�E"#!&%&'���X0XI:H�;:128�5H12�45I8�/07:1�G5H0��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>Z[�#&�"AA%.%"&)�E"#!&%&'�#E'*!%)F,�A*!�+%&#!D�A""$A*!?#!$�&"B!#E�&")?*!T(���9I:1XI1�G5H08�XI:H\I1�G6128�]:O I7_�]<�_<�75:1��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>ZV�*-"!#)%*&#E�$%'%)#E%C#)%*&�#&$�*-"!#)%&'�-"!A*!,#&."�#&�#&#ED(%(�*A�)#%?#&(�(*.%#E�?*!T�%&$B()!D���9;03H12�JI18�7501390�JI08�75I123/0�75618�7561235012�O4:I��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>MZ�-!"$%.#)%*&�#&$�.*&)!*E�*A�.F#*)%.�.F#!#.)"!%()%.(�+D�)F"�,#R%,B,�ED#-B&*@�"R-*&"&)(�%&�-%,�A%EE%&'�-!*."((���9I12�JI8�/0:139I:1�JI18�90:1�G5:12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>M>�"AA".)�A#.)*!(�*A�.F%&#a(�%&$B()!D�()!B.)B!"�+#("$�*&�!"$B&$#&.D�#&#ED(%(���5H123/I12�JI8�/0:13/I12�75I8�9I:3JI1�JI��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>bW�,#-!"$B."N#-!%*!%�#E'*!%)F,�B&$"!�.E*B$�.*,-B)%&'�"&@%!*&,"&)���X063G5H0�75:12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>bL�-"!A*!,#&."�"@#EB#)%*&�*A�%&&*@#)%*&�&")?*!TN+#("$�.!*((N!"'%*&#E�%&&*@#)%@"�.**-"!#)%*&���5:I3901�9I:12��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>[M�!%(T�A#.)*!(�#&#ED(%(�A*!�E*'%()%.(�%&A*!,#)%*&�%&)"'!#)%*&�+#("$�*&�)F"�%,-!*@"$�#F-�N�$",#)"E�,")F*$���/I12�\08�/:39I12�J0��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>[P�.EB()"!%&'�#&#ED(%(�*A�%&-B)�#&$�*B)-B)�*A�(.%"&."�#&$�)".F&*E*'D�+#("$�*&�A"#)B!"�("E".)%*&���SH123K6I�JI8�UI1�JI0��<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<�>=[�

Page 10: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

����� ������������� ��������� ��� �������������������������������������� �������������������� ����������!"#"$!%&�'(�)&"�#"*"%)+'(�,'-"*�.'!�'(*+("�,"!%&$(-+#"�/$#"-�'(�!'01&�#")���23456�7368�93:;4<3=�>?@=��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BCD�#)0-E�'(�)&"�)!$..+%�.*'F�0(-"!�G""HI!+1&)I"J%"H)I)'IH$##�!0*"�/$#"-�'(�%"**0*$!�$0)',$)$�,'-"*���93:;4K:=L�5:=L8�M6=4K@=L�73��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BBB�.$0*)�)'*"!$()�%'()!'*�.'!�#+(10*$!�('(*+("$!�#E#)",�,'-"*�'.�.$0*)�-+$1('#+#�/$#"-�'(�'/#"!N"!���73456=�5:=L8�93:;473=L�>6=8�?:34O6;�?@��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BPQ�,")&'-�'.�!'%G�/'*)#�H$!$,")"!#�-")"%)+'(�/$#"-�'(�&$!,'(+%�F$N"*")�H$%G")�)!$(#.'!,���93:;456=�>6=8�2?3456:=�R:=L8�K@=L4=3=L�O:=L8�R@34K:=L�73��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BPS�!"#"$!%&�'(�!')$!E�'/T"%)�!"%'1(+)+'(�)"%&(+U0"�/$#"-�'(�("0!$*�(")F'!G���>64M6:=�M3:8�V:;�R:=L8�5:=4W3=L�X63��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BSY�!'/0#)�& �%'()!'*�.'!�0(%"!)$+(�#F+)%&"-�('(*+("$!�#+(10*$!�#E#)",#�N+$�*,+�$HH!'$%&���=:�7368�M34Z3=L�Z368�734M6=�2?:=L��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BD[�)&"�,$)&",$)+%$*�,'-"*�$(-�$*1'!+)&,�'.�-+#)!+/0)+'(�(")F'!G�'H)+,+\$)+'(�H!'/*",#���9364?@=L�2?:;8�734<3=�<3��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�BDB�$($*E#+#�& �('!,�.'�.!$%)+'($*�'!-"!�#E#)",�/$#"-�'(�*,+���?;=L45:=�<:8�M34Z3=L�Z36��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�P[]�!"#"$!%&�$(-�+,H!'N","()�'.�-N&'H�*'%$*+\$)+'(�$*1'!+)&,�+(�F+!"*"##�#"(#'!�(")F'!G#���?634<3=�X638�5:4K:=L�R:=L8�M3=493=L�7368�734=:�736��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�P[S�$#E,H)')+%$*�#)$/+*+\$)+'(�'.�('(*+("$!�0(%"!)$+(�.!$%)+'($*I'!-"!�#E#)",���564_@�M38�M34Z3=L�Z36��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PQY�$-$H)+N"�/"$,�#"*"%)+'(�$*1'!+)&,�/$#"-�'(�'HH'!)0(+#)+%�/"$,.'!,+(1���M3:�>68�R@3<3=�?;68�M3=L�R:=L��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�P][�$�,")&'-�)'�.0\\E�,0*)+I'/T"%)+N"�H!'/*",#�0(-"!�!$(-',�"(N+!'(,"()����@ 3X�XA�XA�V>:=L8�M3=L4_6;�M3@8�X?@=493:�M3=�AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�P]C�".."%)�!'01&�-"1!""�$(-�+)#�$HH*+%$)+'(�+(�$))!+/0)"�!"-0%)+'(���K:4X?:;�738�M3=4=3=L�5:=L��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PaQ�!"#"$!%&�'.�$(�+,H!'N"-�H$!)+%*"�.+*)"!�$*1'!+)&,���5;=L4R@3�738�<3=L493=L�X?@=��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PaP�'(�,0*)+I1!$(0*$)+'(�1!$-"-�%'N"!+(1�!'01&�#")#���?;=L�R:=L8�Z34M3:�?6��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PY]�/$#+%�H!'H"!)+"#�'.�.0\\E�$HH!'J+,$)+'(�'H"!$)'!#�0(-"!�%'(#+#)"()�.0(%)+'(#���@A�XA�X�V>:=L8�X?:=L2?;=L�R:=L�5:=L�_68�Z3:=L�?@�AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PYS�)&"�%',H$!$)+N"�#)0-E�'.�.0\\E�!'01&�!"-0%)+'(���@ 3X�XAXA�V>:=L8�>656=�2?:;��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PCa�%'(N'*0)+'(I/$#"-�,"$(#�'.�1!$-+"()�.'!�.$#)�"E"�%"()"!�*'%$*+\$)+'(���?:34b3=�X:38�?63�568�X?6=45:=�5:;8�>?@=45;=L�X?@=8�?;=L4?:3�736��AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA�PCD�

Page 11: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

����� ������������� ��������� ��� �������������������������������������� �������������������� ����������!"�#$%&$'%(�#"�('")�*#(%&�+#&%,!-.'"/�0%.1#)-���23456784�9:87;�<:83�=>;�?37�?@7�?87;�A7B�C3�D345��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FGH�!�1IJ&')�0#)%K�.#�&%-#K$%�!'&,&!+.�.&!,.'&�-L**K'%&M-�-%K%,.'#"�*&#JK%0�+&#0�!�+'"!",'!K�*%&-*%,.'$%���9:78NO345�2>;�9:845N2:>�B>;�9:745NB@O�9:845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FFP�.1%�*!&Q'"/�-%&$',%�RL!K'.I�!")�0!"!/%0%".S�)'/'.!K�'0!/%�*&#,%--'"/�!**K',!.'#"�+#&�0#.#&,I,K%�,#L".'"/���9:@45NA>45�9:>45;�78>NT>@4�9:>45;�U>45N:8>�D845;�9:745NB@O�9:845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FFF�!�$%1',K%�.&!"-$%&-%�!L.#0!.',�*!&Q'"/�!LV'K'!&I�-I-.%0���:27N9:>84�:>845;�U345N:>7�:@;�W@45�?74��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FXY�.1%�!K/#&'.10�#+�0#'-.L&%�0%!-L&%0%".�!**KI'"/�$#KL0%.&',�0%.1#)���U>4N2:@45�B7@4;�?7N9:@45�:27@:���EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FYZ�.#*',�#*.'0'[!.'#"�0%.1#)�J!-%)�#"�K!*K!,%�-,#&%���U845�=783;�U>=74�\745��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�FYF�'0*&#$%)�%RL'K'J&'L0�*#'".�!K/#&'.10�#+�K'"%!&�J'K%$%K�*&#/&!00'"/���W845NU>84�?7;�5>3N?7�<:845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�X]Y�'0*&#$%)�/%"%.',�!K/#&'.10�!")�'.-�!**K',!.'#"�'"�*#(%&�)'-*!.,1�#+�('")�.L&J'"%-����5>3N:>845�?7;�5>3N?7�<:845;�?@NW@45�<:845�EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XPH�.1%�)%-'/"�#+�!�0LK.',#",%*.�'0!/%�&%.&'%$!K�-I-.%0�J!-%)�#"�1!)##*�!")�/00���2:>3�D845;�67846784�D845;�6745�D845�EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�X_]�!�"%(�&%-!0*K'"/�0%.1#)�#+�'0J!K!",%)�K!&/%�)!.!�J!-%)�#"�,K!--�J#L")!&I����=745�2:@45;�<:87�6>4:87;�D845�=783?84;�U>84�745��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�X_G�/&!"LK!&�-.&L,.L&%-�#+�+L[[I�&#L/1�-%.-�J!-%)�#"�/%"%&!K�+L[[I�&%K!.'#"-���=783�<:845;�9:845N?74�@7;�\@N5845�9:@4��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XZ_�!J"#&0!K�#Ja%,.'$%�&%,#/"'.'#"�'"�$')%#�J!-%)�#"�)!.!�0'"'"/�#+�+'"!",%�'")L-.&I���<:7ND845�67845;�:345N=78�<:845�EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XZX�'")L,.'#"�#+�.#K%&!",%�&#L/1�+L[[I�)%,'-'#"�.&%%���6>4N:87�<:87;�2:83N=745�:3>;�2>NW845�<:845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XbZ�.1%�+!'KL&%�!"!KI-'-�#+�%V.&%0%�K%!&"'"/�0!,1'"%�#"�J'/�)!.!�!")�.1%�,#L".%&0%!-L&%���C@7N<:3>�<:845;�2:7N=74�<:83;�=7N<:83�D845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XbY�.1%�.1&%%(!I�#Ja%,.�#&'%".%)�,#",%*.�K!..',%�!")�.1%�.1&%%(!I�*&#*%&.I�#&'%".%)�,#",%*.�K!..',%���?745�D@7;�B745�T784��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XHb�!..&'JL.%�&%)L,.'#"�$'!�+L[[I�&#L/1�-%.-���9:845<:345�D845;�U8?7�T7;�T7845�:@��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XG]�&%-%!&,1�#"�#&)'"!K�&%/&%--'#"�#+�'".%&$!K�$!KL%)�)!.!���:345�<:>;�6>4N:87�<:87;�2>NW845�<:845��EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE�XGG�'")L,.'#"�#+�+L[[I�)%,'-'#"�.&%%�J!-%)�#"�+L[[I�-'0'K!&'.I�&%K!.'#"-1'*�

Page 12: 2015 International Conference on Machine Learning and ...toc.proceedings.com/28487webtoc.pdf · fei-jiang li, yu-hua qian, jie-ting wang, ji-ye liang ..... 58 research on key technologies

����� ������������� ��������� ��� �������������������������������������� �������������������� ������������!"#$%&#'�()*#'+�'*,$-,"�.*#'+�/"#$%&#�0)&#��11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�234�5�6789:65;<�=>8::9?8@5AB�><=8@@<B?56A8B�C8>�=8D?�:65>6�E>8FD<@�AB�=GF<>9EHG:A=5D�:G:6<@:���I*#I*#�J,"+�/,#'/,#'�0*K+�-,*KJ&,�J,*#'+�.&#%&#'�J,��1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�23L�?<=A:A8B�CM:A8B�C8>�<<;9F5:<?�<@86A8B�><=8;BA6A8B���N)"*,�.*#'+�/,*0)&#�O"+�P",%&#'�-"��111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�22Q�@A=>8FD8;;AB;�<@8A68B�=D5::ACA=56A8B�F5:<?�8B�@MD6A9=D5::ACA<>�AB6<;>56A8B�:6>56<;G���()*K$R"�.*#'+�P",$%&#'�-"+�R"�()K"��11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�2ST�F886:6>5EEAB;9F5:<?�><D56A8B�<U6>5=6A8B�AB�CAB5B=A5D�?8@5AB���V,#'�WK#'+�P",$%&#'�-"+�OK#'$R,#�."��1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�2S3��HGE<>:EH<>A=5D�<@F<??AB;�A6<>56AX<�YM5B6AZ56A8B�H5:HAB;����(),!,*#�)"*#'+�(),!,*#�)"*#'+�R"&[,#'�J\+�.,#'�.1R1�#'�1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�ST]�D<5>BAB;�E<>C8>@5B=<�8C�?5;:X@�5D;8>A6H@�F5:<?�8B�@5> 8X�:5@EDAB;���/,&�-"+�R*#'�J"+�V,#�(K"��111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�S_T�B8X<D�A@EM656A8B�C8>�6A@<�:<>A<:�?565���0),*$R*#'�0)*#'+�0)&#'$P"�.*#'+�N),&$/"&�J&&��1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111�S_L��