machine learning - researchr tag

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2012

A Study on the Effect of Regularization Matrices in Motion EstimationAlessandra Martins Coelho, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela. International Journal of Computer Applications, 51(19):17-24, 2012. [doi]

2011

Effective End-User Interaction with Machine LearningSaleema Amershi, James Fogarty, Ashish Kapoor, Desney S. Tan. AAAI 2011: [doi]

Human-Guided Machine Learning for Fast and Accurate Network Alarm TriageSaleema Amershi, Bongshin Lee, Ashish Kapoor, Ratul Mahajan, Blaine Christian. IJCAI 2011: 2564-2569 [doi]

An Adaptive Machine Learning Algorithm for Location PredictionTheodoros Anagnostopoulos, Christos Anagnostopoulos, Stathes Hadjiefthymiades. ijwin, 18(2):88-99, 2011. [doi]

Application of machine learning techniques to analyse student interactions and improve the collaboration processAntonio R. Anaya, Jesus Boticario. eswa, 38(2):1171-1181, 2011. [doi]

Machine learning techniques applied to the construction of a new geomechanical quality indexM. Araújo, José M. Matías, T. Rivas, Javier Taboada. ijcm, 88(9):1830-1838, 2011. [doi]

Application of error minimized extreme learning machine for simultaneous learning of a function and its derivativesS. Balasundaram, Kapil. ijon, 74(16):2511-2519, 2011. [doi]

Predicting Breast Screening Attendance Using Machine Learning TechniquesVikraman Baskaran, Aziz Guergachi, Rajeev K. Bali, Raouf N. Gorgui-Naguib. titb, 15(2):251-259, 2011. [doi]

Stochastic simulation and modelling of metabolic networks in a machine learning frameworkMarenglen Biba, Fatos Xhafa, Floriana Esposito, Stefano Ferilli. simpra, 19(9):1957-1966, 2011. [doi]

Using Machine Learning Techniques for Modelling and Simulation of Metabolic NetworksMarenglen Biba, Fatos Xhafa, Floriana Esposito, Stefano Ferilli. cisis 2011: 85-92 [doi]

Embracing Uncertainty: Applied Machine Learning Comes of AgeChristopher M. Bishop. pkdd 2011: 4 [doi]

Manifold Learning for Visualization of Vibrational States of a Rotating MachineIgnacio Díaz Blanco, Abel A. Cuadrado Vega, Alberto B. Diez, Manuel Domínguez-González. icann 2011: 285-292 [doi]

Measure Transformer Semantics for Bayesian Machine LearningJohannes Borgström, Andrew D. Gordon, Michael Greenberg, James Margetson, Jurgen Van Gael. ESOP 2011: 77-96 [doi]

Using statistical and machine learning to help institutions detect suspicious access to electronic health recordsAziz A. Boxwala, Jihoon Kim, Janice M. Grillo, Lucila Ohno-Machado. jamia, 18(4):498-505, 2011. [doi]

Learning with Support Vector MachinesColin Campbell, Yiming Ying. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, 2011. [doi]

Composite Function Wavelet Neural Networks with Differential Evolution and Extreme Learning MachineJiuwen Cao, Zhiping Lin, Guang-Bin Huang. npl, 33(3):251-265, 2011. [doi]

Apolo: making sense of large network data by combining rich user interaction and machine learningDuen Horng Chau, Aniket Kittur, Jason I. Hong, Christos Faloutsos. CHI 2011: 167-176 [doi]

Improved Learning of Gaussian-Bernoulli Restricted Boltzmann MachinesKyungHyun Cho, Alexander Ilin, Tapani Raiko. icann 2011: 10-17 [doi]

Special Issue on Hybrid and Ensemble Methods in Machine LearningOscar Cordón, Przemyslaw Kazienko, Bogdan Trawinski. ngc, 29(3):241-244, 2011. [doi]

Statistical atlases and machine learning tools applied to optimized prostate biopsy for cancer detection and estimation of volume and Gleason scoreChristos Davatzikos. isbi 2011: 2107-2108 [doi]

Privacy and Security Issues in Data Mining and Machine Learning - International ECML/PKDD Workshop, PSDML 2010, Barcelona, Spain, September 24, 2010. Revised Selected PapersChristos Dimitrakakis, Aris Gkoulalas-Divanis, Aikaterini Mitrokotsa, Vassilios S. Verykios, Yücel Saygin, editors, Volume 6549 of Lecture Notes in Computer Science, Springer, 2011. [doi]

DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learningJesse Eickholt, Xin Deng, Jianlin Cheng. bmcbi, 12:43, 2011. [doi]

MELM-GRBF: A modified version of the extreme learning machine for generalized radial basis function neural networksFrancisco Fernández-Navarro, César Hervás-Martínez, Javier Sánchez-Monedero, Pedro Antonio Gutiérrez. ijon, 74(16):2502-2510, 2011. [doi]

Implementing reliable learning through Reliable Support Vector MachinesEnrico Ferrari, Marco Muselli. foci 2011: 100-106 [doi]

The Machine Learning journal: 25 years youngPeter A. Flach. ml, 82(3):273-274, 2011. [doi]

Self-learning visual inspection system for cable crimping machinesStefano Ghidoni, Matteo Finotto, Emanuele Menegatti. icra 2011: [doi]

SystemML: Declarative machine learning on MapReduceAmol Ghoting, Rajasekar Krishnamurthy, Edwin P. D. Pednault, Berthold Reinwald, Vikas Sindhwani, Shirish Tatikonda, Yuanyuan Tian, Shivakumar Vaithyanathan. icde 2011: 231-242 [doi]

Machine learning for computer security: A guide to prospective authorsGiorgio Giacinto, Belur V. Dasarathy. inffus, 12(3):238-239, 2011. [doi]

High Classification Rates for Continuous Cow Activity Recognition Using Low-Cost GPS Positioning Sensors and Standard Machine Learning TechniquesTorben Godsk, Mikkel Baun Kjærgaard. incdm 2011: 174-188 [doi]

Two kinesthetic learning activities: turing machines and basic computer organizationMichael Goldweber. iticse 2011: 335 [doi]

Realtime Encrypted Traffic Identification using Machine LearningChengjie Gu, Shunyi Zhang, Yanfei Sun. jsw, 6(6):1009-1016, 2011. [doi]

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part IIDimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis, editors, Volume 6912 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part IDimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis, editors, Volume 6911 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part IIIDimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis, editors, Volume 6913 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Laplacian Support Vector Machines with Multi-Kernel LearningLihua Guo, Lianwen Jin. ieicet, 94-D(2):379-383, 2011. [doi]

Learning Readers News Preferences with Support Vector MachinesElena Hensinger, Ilias N. Flaounas, Nello Cristianini. icannga 2011: 322-331 [doi]

Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part IITimo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski, editors, Volume 6792 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part ITimo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski, editors, Volume 6791 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Introduction to special issue on large-scale machine learningChun-Nan Hsu. tist, 2(3):25, 2011. [doi]

Advances in extreme learning machines (ELM2010)Guang-Bin Huang, Dianhui Wang. ijon, 74(16):2411-2412, 2011. [doi]

Single-machine group scheduling with both learning effects and deteriorating jobsXue Huang, Ming-Zheng Wang, Ji-Bo Wang. candie, 60(4):750-754, 2011. [doi]

Machine Learning and AgentsPiotr Jedrzejowicz. kesamsta 2011: 2-15 [doi]

Machine learning study for the prediction of transdermal peptideEunkyoung Jung, Seung Hoon Choi, Nam-Kyung Lee, Sang-Kee Kang, Yun-Jaie Choi, Jae-Min Shin, Kihang Choi, Dong-Hyun Jung. jcamd, 25(4):339-347, 2011. [doi]

Classification of ECG Signals Using Extreme Learning MachineS. Karpagachelvi, M. Arthanari, M. Sivakumar. ccsecis, 4(1):42-52, 2011. [doi]

A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search ProblemsLars Kotthoff, Ian P. Gent, Ian Miguel. socs 2011: [doi]

Some unrelated parallel machine scheduling problems with past-sequence-dependent setup time and learning effectsWen-Hung Kuo, Chou-Jung Hsu, Dar-Li Yang. candie, 61(1):179-183, 2011. [doi]

Filtering artificial texts with statistical machine learning techniquesThomas Lavergne, Tanguy Urvoy, François Yvon. lre, 45(1):25-43, 2011. [doi]

A note on single-machine scheduling with general learning effect and past-sequence-dependent setup timeWen-Chiung Lee. cma, 62(4):2095-2100, 2011. [doi]

Advances in artificial neural networks, machine learning, and computational intelligenceJohn A. Lee, Frank-Michael Schleif, Thomas Martinetz. ijon, 74(9):1299-1300, 2011. [doi]

Introduction to special issue on machine learning for adaptivity in spoken dialogue systemsOliver Lemon, Olivier Pietquin. tslp, 7(3):3, 2011. [doi]

The use of hybrid manifold learning and support vector machines in the prediction of business failureFengyi Lin, Ching-Chiang Yeh, Meng-Yuan Lee. kbs, 24(1):95-101, 2011. [doi]

Introduction to special issue on machine learning for business applicationsCharles X. Ling. tist, 2(3):18, 2011. [doi]

Developing Prognosis Tools to Identify Learning Difficulties in Children Using Machine Learning TechnologiesAntonis Loizou, Yiannis Laouris. cogcom, 3(3):490-500, 2011. [doi]

Comparing machine learning classifiers in potential distribution modellingAna Carolina Lorena, Luís F. O. Jacintho, Marinez Ferreira de Siqueira, Renato De Giovanni, Lúcia G. Lohmann, André Carlos Ponce Leon Ferreira de Carvalho, Missae Yamamoto. eswa, 38(5):5268-5275, 2011. [doi]

Learning patterns in combinatorial protein libraries by Support Vector MachinesSridhar Maddipati, Ravi Nandigam, Sangtae Kim, Venkat Venkatasubramanian. cce, 35(6):1143-1151, 2011. [doi]

Enhancing a Fuzzy Logic Inference Engine through Machine Learning for a Self- Managed NetworkPanagis Magdalinos, Apostolos Kousaridas, Panagiotis Spapis, George Katsikas, Nancy Alonistioti. monet, 16(4):475-489, 2011. [doi]

Application of extreme learning machine for series compensated transmission line protectionV. Malathi, N. S. Marimuthu, S. Baskar, K. Ramar. eaai, 24(5):880-887, 2011. [doi]

Fusion of learning automata theory and granular inference systems: ANLAGIS. Applications to pattern recognition and machine learningDarío Maravall, Javier de Lope Asiaín. ijon, 74(8):1237-1242, 2011. [doi]

Passive-Aggressive for On-Line Learning in Statistical Machine TranslationPascual Martínez-Gómez, Germán Sanchis-Trilles, Francisco Casacuberta. ibpria 2011: 240-247 [doi]

Fast cell detection in high-throughput imagery using GPU-accelerated machine learningDavid Mayerich, Jaerock Kwon, Aaron Panchal, John Keyser, Yoonsuck Choe. isbi 2011: 719-723 [doi]

Machine learning in space: extending our reachAmy McGovern, Kiri L. Wagstaff. ml, 84(3):335-340, 2011. [doi]

Learning about Machine Learning: An Extended Assignment to Classify Twitter AccountsEni Mustafaraj, Scott D. Anderson. flairs 2011: [doi]

Information Hiding by Machine Learning: A Method of Key Generation for Information Extracting Using Neural NetworkKensuke Naoe, Hideyasu Sasaki, Yoshiyasu Takefuji. ijoci, 2(1):21-48, 2011. [doi]

Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine TranslationYizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan. jmlr, 12:1-30, 2011. [doi]

An Interactive Machine Translation System with Online LearningDaniel Ortiz-Martínez, Luis A. Leiva, Vicent Alabau, Ismael García-Varea, Francisco Casacuberta. acl 2011: 68-73 [doi]

Fault tolerant machine learning for nanoscale cognitive radioJoni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo. ijon, 74(5):753-764, 2011. [doi]

Recent advances on machine learning and CyberneticsWitold Pedrycz, Daniel S. Yeung, Xizhao Wang. soco, 15(6):1039, 2011. [doi]

Machine Learning and Data Mining in Pattern Recognition - 7th International Conference, MLDM 2011, New York, NY, USA, August 30 - September 3, 2011. ProceedingsPetra Perner, editor, Volume 6871 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 9th European Conference, EvoBIO 2011, Torino, Italy, April 27-29, 2011. ProceedingsClara Pizzuti, Marylyn D. Ritchie, Mario Giacobini, editors, Volume 6623 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Student Speech Act Classification Using Machine LearningTravis Rasor, Andrew Olney, Sidney K. D Mello. flairs 2011: [doi]

Learning message-passing inference machines for structured predictionStéphane Ross, Daniel Munoz, Martial Hebert, J. Andrew Bagnell. cvpr 2011: 2737-2744 [doi]

Improving the prediction of disulfide bonds in Eukaryotes with machine learning methods and protein subcellular localizationCastrense Savojardo, Piero Fariselli, Monther Alhamdoosh, Pier Luigi Martelli, Andrea Pierleoni, Rita Casadio. bioinformatics, 27(16):2224-2230, 2011. [doi]

A large scale machine learning system for recommending heterogeneous content in social networksYanxin Shi, David Ye, Andrey Goder, Srinivas Narayanan. sigir 2011: 1337-1338 [doi]

Machine learning for information retrievalLuo Si, Rong Jin. sigir 2011: 1293-1294 [doi]

BELM: Bayesian Extreme Learning MachineEmilio Soria-Olivas, Juan Gómez-Sanchís, José David Martín-Guerrero, Joan Vila-Francés, Marcelino Martínez-Sober, José Rafael Magdalena Benedito, Antonio J. Serrano. tnn, 22(3):505-509, 2011. [doi]

On the use of machine learning methods for modern drug discoveryAxel J. Soto. aicom, 24(1):99-100, 2011. [doi]

The application of stochastic machine learning methods in the prediction of skin penetrationYi Sun, Marc B. Brown, Maria Prapopoulou, Neil Davey, Rod Adams, Gary P. Moss. asc, 11(2):2367-2375, 2011. [doi]

A Machine Learning and Data Mining Framework to Enable Evolutionary Improvement in Trauma TriageDouglas A. Talbert, Matt Honeycutt, Steve Talbert. mldm 2011: 348-361 [doi]

Joint reply to the erratum and the note on Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning [Math. Comput. Modelling 50 (2009) 401-406]M. Duran Toksari, Daniel Oron, Ertan Güner. mcm, 54(1-2):849-851, 2011. [doi]

A branch and bound algorithm for minimizing makespan on a single machine with unequal release times under learning effect and deteriorating jobsM. Duran Toksari. cor, 38(9):1361-1365, 2011. [doi]

On Efficient Learning Machine With Root-Power Mean Neuron in Complex DomainBipin Kumar Tripathi, Prem Kumar Kalra. tnn, 22(5):727-738, 2011. [doi]

The Power of Declarative Languages: From Information Extraction to Machine LearningShivakumar Vaithyanathan. btw 2011: 23

Hitoshi Iba, Topon Kumar Paul, Yoshohiko Hasegawa: Applied genetic programming and machine learning - CRC Press, 327 pp, ISBN: 978-1-4398-0369-1Kalyan Veeramachaneni. gpem, 12(2):179-180, 2011. [doi]

A study on effectiveness of extreme learning machineYuguang Wang, Feilong Cao, Yubo Yuan. ijon, 74(16):2483-2490, 2011. [doi]

Image deblurring with filters learned by extreme learning machineLiang Wang, Yaping Huang, Xiaoyue Luo, Zhe Wang, Siwei Luo. ijon, 74(16):2464-2474, 2011. [doi]

Single-machine scheduling jobs with exponential learning functionsJi-Bo Wang, Jian-Jun Wang. candie, 60(4):755-759, 2011. [doi]

Erratum to Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning [Math. Comput. Modelling 50 (2009) 401-406]Xiao-yuan Wang, Li-Yan Wang, Ji-Bo Wang. cma, 61(5):1471-1473, 2011. [doi]

A revision of machine scheduling problems with a general learning effectJi-Bo Wang, Ming-Zheng Wang. mcm, 53(1-2):330-336, 2011. [doi]

Erratum to Notes on Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning [Math. Comput. Modelling 50 (2009) 401-406] [CAMWA 61/5 (2011) 1471-1473]Xiao-yuan Wang, Li-Yan Wang, Ji-Bo Wang. cma, 61(10):3180, 2011. [doi]

Mammogram retrieval through machine learning within BI-RADS standardsChia-Hung Wei, Yue Li, Pai Jung Huang. jbi, 44(4):607-614, 2011. [doi]

Some single-machine scheduling problems with a truncation learning effectChin-Chia Wu, Yunqiang Yin, Shuenn-Ren Cheng. candie, 60(4):790-795, 2011. [doi]

A hierarchical multiclass support vector machine incorporated with holistic triple learning unitsXiao-Lei Xia, Kang Li, George W. Irwin. soco, 15(5):833-843, 2011. [doi]

Structural learning of the Boltzmann machine and its application to life cycle managementShamshul Bahar Yaakob, Junzo Watada, John Fulcher. ijon, 74(12-13):2193-2200, 2011. [doi]

A note on Single-machine scheduling with general learning functions Na Yin, Xue Huang. cma, 61(9):2929-2930, 2011. [doi]

Notes on some single-machine scheduling problems with general position-dependent and time-dependent learning effects Yunqiang Yin, Dehua Xu, Xiaokun Huang. isci, 181(11):2209-2217, 2011. [doi]

Notes on The common due-date early/tardy scheduling problem on a parallel machine under the effects of time-dependent learning and linear and nonlinear deterioration Yunqiang Yin, Dehua Xu, Xiaokun Huang. eswa, 38(7):9030-9031, 2011. [doi]

Notes on Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning Yunqiang Yin, Dehua Xu. mcm, 54(1-2):846-848, 2011. [doi]

Some single-machine scheduling problems with general effects of learning and deteriorationYunqiang Yin, Dehua Xu. cma, 61(1):100-108, 2011. [doi]

Single-machine group scheduling with resource allocation and learning effectZhanguo Zhu, Linyan Sun, Feng Chu, Ming Liu. candie, 60(1):148-157, 2011. [doi]

Using focal point learning to improve human-machine tacit coordinationInon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschein. AAMAS, 22(2):289-316, 2011. [doi]

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