Papers
Deep Poisson Factor Modeling
Ricardo Henao, Zhe Gan, James Lu et al.
Discriminative Robust Transformation Learning
Jiaji Huang, Qiang Qiu, Guillermo Sapiro et al.
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
Marijn F Stollenga, Wonmin Byeon, Marcus Liwicki et al.
Column Selection via Adaptive Sampling
Saurabh Paul, Malik Magdon-Ismail, Petros Drineas
Smooth Interactive Submodular Set Cover
Bryan D He, Yisong Yue
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
Mijung Park, Wittawat Jitkrittum, Ahmad Qamar et al.
Online F-Measure Optimization
Róbert Busa-Fekete, Balázs Szörényi, Krzysztof Dembczynski et al.
Deep learning with Elastic Averaging SGD
Sixin Zhang, Anna E Choromanska, Yann LeCun
Optimal Rates for Random Fourier Features
Bharath Sriperumbudur, Zoltan Szabo
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning
Jiajun Wu, Ilker Yildirim, Joseph J. Lim et al.
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra et al.
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters
Emmanuel Abbe, Colin Sandon
Convolutional spike-triggered covariance analysis for neural subunit models
Anqi Wu, ll Memming Park, Jonathan W Pillow
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors
Sohail Bahmani, Justin Romberg
Smooth and Strong: MAP Inference with Linear Convergence
Ofer Meshi, Mehrdad Mahdavi, Alex Schwing
Deep Convolutional Inverse Graphics Network
Tejas D Kulkarni, William F. Whitney, Pushmeet Kohli et al.
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani, Yoav Freund
Online Prediction at the Limit of Zero Temperature
Mark Herbster, Stephen Pasteris, Shaona Ghosh
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
Tom Goldstein, Min Li, Xiaoming Yuan
Distributionally Robust Logistic Regression
Soroosh Shafieezadeh-Abadeh, Peyman Mohajerin Esfahani, Daniel Huhn
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli et al.
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors
Andrea Montanari, Daniel Reichman, Ofer Zeitouni
Bounding errors of Expectation-Propagation
Guillaume P Dehaene, Simon Barthelmé
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
Sorathan Chaturapruek, John C. Duchi, Christopher Ré