Papers
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.
Equilibrated adaptive learning rates for non-convex optimization
Yann Dauphin, Harm de Vries, Yoshua Bengio
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Vitaly Kuznetsov, Mehryar Mohri
Convergence rates of sub-sampled Newton methods
Murat A Erdogdu, Andrea Montanari
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang, Fangjian Guo, Katherine A. Heller et al.
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
Eunho Yang, Aurelie C. Lozano
No-Regret Learning in Bayesian Games
Jason Hartline, Vasilis Syrgkanis, Eva Tardos
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David
M-Best-Diverse Labelings for Submodular Energies and Beyond
Alexander Kirillov, Dmytro Shlezinger, Dmitry P Vetrov et al.
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
Amir Dezfouli, Edwin V. Bonilla