Papers
Structured output regression for detection with partial truncation
Andrea Vedaldi, Andrew Zisserman
On Stochastic and Worst-case Models for Investing
Elad Hazan, Satyen Kale
From PAC-Bayes Bounds to KL Regularization
Pascal Germain, Alexandre Lacasse, Mario Marchand et al.
Linear-time Algorithms for Pairwise Statistical Problems
Parikshit Ram, Dongryeol Lee, William March et al.
Information-theoretic lower bounds on the oracle complexity of convex optimization
Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett et al.
Which graphical models are difficult to learn?
Andrea Montanari, Jose A. Pereira
Heavy-Tailed Symmetric Stochastic Neighbor Embedding
Zhirong Yang, Irwin King, Zenglin Xu et al.
Filtering Abstract Senses From Image Search Results
Kate Saenko, Trevor Darrell
Matrix Completion from Power-Law Distributed Samples
Raghu Meka, Prateek Jain, Inderjit S. Dhillon
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process
Finale Doshi-velez, Shakir Mohamed, Zoubin Ghahramani et al.
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism
Douglas Eck, Yoshua Bengio, Aaron C. Courville
Modeling the spacing effect in sequential category learning
Hongjing Lu, Matthew Weiden, Alan L. Yuille
Sparse Estimation Using General Likelihoods and Non-Factorial Priors
David P. Wipf, Srikantan S. Nagarajan
Factor Modeling for Advertisement Targeting
Ye Chen, Michael Kapralov, John Canny et al.
A Stochastic approximation method for inference in probabilistic graphical models
Peter Carbonetto, Matthew King, Firas Hamze
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution
Cosmin Bejan, Matthew Titsworth, Andrew Hickl et al.
Streaming Pointwise Mutual Information
Benjamin V. Durme, Ashwin Lall
Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation
Jie Luo, Barbara Caputo, Vittorio Ferrari
Sensitivity analysis in HMMs with application to likelihood maximization
Pierre-arnaud Coquelin, Romain Deguest, Rémi Munos
Semi-Supervised Learning in Gigantic Image Collections
Rob Fergus, Yair Weiss, Antonio Torralba
Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition
Natasha Singh-miller, Michael Collins
Zero-shot Learning with Semantic Output Codes
Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton et al.
Bilinear classifiers for visual recognition
Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes
Gaussian process regression with Student-t likelihood
Jarno Vanhatalo, Pasi Jylänki, Aki Vehtari
Potential-Based Agnostic Boosting
Varun Kanade, Adam Kalai