Papers
Compressive spectral embedding: sidestepping the SVD
Dinesh Ramasamy, Upamanyu Madhow
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
Ofer Dekel, Ronen Eldan, Tomer Koren
Particle Gibbs for Infinite Hidden Markov Models
Nilesh Tripuraneni, Shixiang (Shane) Gu, Hong Ge et al.
A Theory of Decision Making Under Dynamic Context
Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen
Learning to Segment Object Candidates
Pedro O O. Pinheiro, Ronan Collobert, Piotr Dollar
Minimax Time Series Prediction
Wouter M. Koolen, Alan Malek, Peter L Bartlett et al.
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Moontae Lee, David Bindel, David Mimno
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen, Ji He, Yelong Shen et al.
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
Fredrik D Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya et al.
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Ryan J Giordano, Tamara Broderick, Michael I Jordan
Learnability of Influence in Networks
Harikrishna Narasimhan, David C. Parkes, Yaron Singer
On the Accuracy of Self-Normalized Log-Linear Models
Jacob Andreas, Maxim Rabinovich, Michael I Jordan et al.
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels
Purnamrita Sarkar, Deepayan Chakrabarti, peter j bickel
Cornering Stationary and Restless Mixing Bandits with Remix-UCB
Julien Audiffren, Liva Ralaivola
Visalogy: Answering Visual Analogy Questions
Fereshteh Sadeghi, C. Lawrence Zitnick, Ali Farhadi
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen, Aditya Menon, Robert C. Williamson
A hybrid sampler for Poisson-Kingman mixture models
Maria Lomeli, Stefano Favaro, Yee Whye Teh
Inverse Reinforcement Learning with Locally Consistent Reward Functions
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Fast and Guaranteed Tensor Decomposition via Sketching
Yining Wang, Hsiao-Yu Tung, Alexander J Smola et al.
Evaluating the statistical significance of biclusters
Jason Lee, Yuekai Sun, Jonathan E Taylor
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian, Yijun Huang, Yuncheng Li et al.
The Human Kernel
Andrew G Wilson, Christoph Dann, Chris Lucas et al.
Probabilistic Variational Bounds for Graphical Models
Qiang Liu, John W. Fisher III, Alex Ihler
Analysis of Robust PCA via Local Incoherence
Huishuai Zhang, Yi Zhou, Yingbin Liang
Optimal Linear Estimation under Unknown Nonlinear Transform
Xinyang Yi, Zhaoran Wang, Constantine Caramanis et al.