Papers
Accelerated Proximal Gradient Methods for Nonconvex Programming
Huan Li, Zhouchen Lin
Accelerated Mirror Descent in Continuous and Discrete Time
Walid Krichene, Alexandre Bayen, Peter L Bartlett
Preconditioned Spectral Descent for Deep Learning
David E Carlson, Edo Collins, Ya-Ping Hsieh et al.
Discrete Rényi Classifiers
Meisam Razaviyayn, Farzan Farnia, David Tse
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Seunghoon Hong, Hyeonwoo Noh, Bohyung Han
Gaussian Process Random Fields
David Moore, Stuart Russell
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Nikhil Rao, Hsiang-Fu Yu, Pradeep K Ravikumar et al.
Skip-Thought Vectors
Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov et al.
Fast Randomized Kernel Ridge Regression with Statistical Guarantees
Ahmed Alaoui, Michael W. Mahoney
Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs
Vidyashankar Sivakumar, Arindam Banerjee, Pradeep K Ravikumar
Stochastic Expectation Propagation
Yingzhen Li, José Miguel Hernández-Lobato, Richard E Turner
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
David I Inouye, Pradeep K Ravikumar, Inderjit S Dhillon
The Poisson Gamma Belief Network
Mingyuan Zhou, Yulai Cong, Bo Chen
HONOR: Hybrid Optimization for NOn-convex Regularized problems
Pinghua Gong, Jieping Ye
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
Vivien Seguy, Marco Cuturi
Matrix Completion Under Monotonic Single Index Models
Ravi Sastry Ganti, Laura Balzano, Rebecca Willett
Learning with Relaxed Supervision
Jacob Steinhardt, Percy Liang
On Elicitation Complexity
Rafael Frongillo, Ian Kash
Variance Reduced Stochastic Gradient Descent with Neighbors
Thomas Hofmann, Aurelien Lucchi, Simon Lacoste-Julien et al.
Learning to Linearize Under Uncertainty
Ross Goroshin, Michael F Mathieu, Yann LeCun
Fast Bidirectional Probability Estimation in Markov Models
Siddhartha Banerjee, Peter Lofgren
Softstar: Heuristic-Guided Probabilistic Inference
Mathew Monfort, Brenden M Lake, Brenden M Lake et al.
Where are they looking?
Adria Recasens, Aditya Khosla, Carl Vondrick et al.
Sum-of-Squares Lower Bounds for Sparse PCA
Tengyu Ma, Avi Wigderson
Active Learning from Weak and Strong Labelers
Chicheng Zhang, Kamalika Chaudhuri