CLASSIC : un projet d’équipe Convex Learning through Aggregation, Supervised Statistical Inference and Classification Olivier Catoni Vincent Rivoirard

Source URL: www.math.ens.fr

Collective Noise Contrastive Estimation for Policy Transfer Learning Weinan Zhang† , Ulrich Paquet‡ , Katja Hofmann‡ † University College London, ‡ Microsoft Research

Source URL: www.ulrichpaquet.com

• Maximum likelihood estimation
• Loss function
• Likelihood function
• Supervised learning
• Machine learning
• Applied mathematics
• Cognition
• Cognitive science

Efficient Non-Parametric Function Induction in Semi-Supervised Learning Olivier Delalleau, Yoshua Bengio and Nicolas Le Roux Dept. IRO, Universit´e de Montr´eal P.O. Box 6128, Succ. Centre-Ville, Montreal, H3C 3J7, Qc,

Source URL: nicolas.le-roux.name

Tractable Semi-Supervised Learning of Complex Structured Prediction Models Kai-Wei Chang1 , S. Sundararajan2 , and S. Sathiya Keerthi3 1 Dept. of Computer Science, University of Illinois at Urbana-Champaign, IL USA

Source URL: www.keerthis.com

IEEE TRANSACTIONS ON SYSTEMS, MAN, AND 455 CYBERNETICS, VOL. SMC-3, NO. 5, SEPTEMBER 1973

Source URL: www-isl.stanford.edu

• Computational statistics
• Machine learning
• Learning
• Artificial intelligence
• Statistics
• Control theory
• Bootstrapping
• Resampling
• Adaptive control
• Supervised learning
• Bootstrap aggregating

CUAB: Supervised Learning of Disorders and their Attributes Using Relations John David Osborne, Steven Bethard University of Alabama at Birmingham 1720 2nd Ave South Birmingham, AL, USA 35294

Source URL: alt.qcri.org

arXiv:1402.3337v2 [stat.ML] 10 NovZero-bias autoencoders and the benefits of co-adapting features Roland Memisevic

Source URL: arxiv.org

• Artificial neural networks
• Machine learning
• Learning
• Artificial intelligence
• Unsupervised learning
• Autoencoder
• Computational neuroscience
• Computational statistics
• Feature learning
• Rectifier
• Restricted Boltzmann machine
• Supervised learning

Revisiting Embedding Features for Simple Semi-supervised Learning † Jiang Guo† , Wanxiang Che† , Haifeng Wang‡ , Ting Liu†∗ Research Center for Social Computing and Information Retrieval Harbin Institute of T

Source URL: ir.hit.edu.cn

25 A Discussion of Semi-Supervised Learning and Transduction The following is a fictitious discussion inspired by real discussions between the editors of

Source URL: olivier.chapelle.cc

Pragmatic Text Mining: Minimizing Human Effort to Quantify Many Issues in Call Logs

Source URL: www.kirshenbaum.net

• Machine learning
• Statistical classification
• Data mining
• Cluster analysis
• Geostatistics
• K-means clustering
• Pattern recognition
• Support vector machine
• Supervised learning
• Naive Bayes classifier
• Determining the number of clusters in a data set
• Semi-supervised learning