Papers
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering
Shinichi Nakajima, Akiko Takeda, S. Derin Babacan et al.
Graphical Models for Inference with Missing Data
Karthika Mohan, Judea Pearl, Jin Tian
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream
Daniel L Yamins, Ha Hong, Charles Cadieu et al.
High-Dimensional Gaussian Process Bandits
Josip Djolonga, Andreas Krause, Volkan Cevher
Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation
Vibhav Vineet, Carsten Rother, Philip Torr
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
Jacob Abernethy, Peter L Bartlett, Rafael Frongillo et al.
Inferring neural population dynamics from multiple partial recordings of the same neural circuit
Srini Turaga, Lars Buesing, Adam M Packer et al.
Information-theoretic lower bounds for distributed statistical estimation with communication constraints
Yuchen Zhang, John Duchi, Michael I Jordan et al.
Integrated Non-Factorized Variational Inference
Shaobo Han, Xuejun Liao, Lawrence Carin
Inverse Density as an Inverse Problem: the Fredholm Equation Approach
Qichao Que, Mikhail Belkin
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals
Barbara Rakitsch, Christoph Lippert, Karsten Borgwardt et al.
k-Prototype Learning for 3D Rigid Structures
Hu Ding, Ronald Berezney, Jinhui Xu
Large Scale Distributed Sparse Precision Estimation
Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh et al.
Lasso Screening Rules via Dual Polytope Projection
Jie Wang, Jiayu Zhou, Peter Wonka et al.
Latent Maximum Margin Clustering
Guang-Tong Zhou, Tian Lan, Arash Vahdat et al.
Latent Structured Active Learning
Wenjie Luo, Alex Schwing, Raquel Urtasun
Learning Adaptive Value of Information for Structured Prediction
David J Weiss, Ben Taskar
Learning a Deep Compact Image Representation for Visual Tracking
Naiyan Wang, Dit-Yan Yeung
Learning and using language via recursive pragmatic reasoning about other agents
Nathaniel J Smith, Noah Goodman, Michael Frank
Learning Chordal Markov Networks by Constraint Satisfaction
Jukka Corander, Tomi Janhunen, Jussi Rintanen et al.
Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions
Tamir Hazan, Subhransu Maji, Joseph Keshet et al.
Learning Feature Selection Dependencies in Multi-task Learning
Daniel Hernández-Lobato, José Miguel Hernández-Lobato
Learning from Limited Demonstrations
Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau et al.