Papers
Learning the context of a category
Dan Navarro
Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models
Congcong Li, Adarsh Kowdle, Ashutosh Saxena et al.
Inference with Multivariate Heavy-Tails in Linear Models
Danny Bickson, Carlos Guestrin
Batch Bayesian Optimization via Simulation Matching
Javad Azimi, Alan Fern, Xiaoli Z. Fern
Multi-Stage Dantzig Selector
Ji Liu, Peter Wonka, Jieping Ye
Learning Efficient Markov Networks
Vibhav Gogate, William Webb, Pedro Domingos
Self-Paced Learning for Latent Variable Models
M. P. Kumar, Benjamin Packer, Daphne Koller
Lower Bounds on Rate of Convergence of Cutting Plane Methods
Xinhua Zhang, Ankan Saha, S.v.n. Vishwanathan
A Discriminative Latent Model of Image Region and Object Tag Correspondence
Yang Wang, Greg Mori
Mixture of time-warped trajectory models for movement decoding
Elaine Corbett, Eric Perreault, Konrad Koerding
Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable
Lauren Hannah, Warren Powell, David M. Blei
Variable margin losses for classifier design
Hamed Masnadi-shirazi, Nuno Vasconcelos
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions
Achintya Kundu, Vikram Tankasali, Chiranjib Bhattacharyya et al.
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
Tamir Hazan, Raquel Urtasun
Word Features for Latent Dirichlet Allocation
James Petterson, Wray Buntine, Shravan M. Narayanamurthy et al.
Brain covariance selection: better individual functional connectivity models using population prior
Gael Varoquaux, Alexandre Gramfort, Jean-baptiste Poline et al.
Probabilistic Deterministic Infinite Automata
David Pfau, Nicholas Bartlett, Frank Wood
Large-Scale Matrix Factorization with Missing Data under Additional Constraints
Kaushik Mitra, Sameer Sheorey, Rama Chellappa
Active Learning Applied to Patient-Adaptive Heartbeat Classification
Jenna Wiens, John V. Guttag
Inductive Regularized Learning of Kernel Functions
Prateek Jain, Brian Kulis, Inderjit S. Dhillon
Active Estimation of F-Measures
Christoph Sawade, Niels Landwehr, Tobias Scheffer
Empirical Bernstein Inequalities for U-Statistics
Thomas Peel, Sandrine Anthoine, Liva Ralaivola
Approximate inference in continuous time Gaussian-Jump processes
Manfred Opper, Andreas Ruttor, Guido Sanguinetti
Synergies in learning words and their referents
Mark Johnson, Katherine Demuth, Bevan Jones et al.