Papers
Unbounded cache model for online language modeling with open vocabulary
Edouard Grave, Moustapha M Cisse, Armand Joulin
Differentially Private Empirical Risk Minimization Revisited: Faster and More General
Di Wang, Minwei Ye, Jinhui Xu
Streaming Sparse Gaussian Process Approximations
Thang D Bui, Cuong Nguyen, Richard E Turner
Preventing Gradient Explosions in Gated Recurrent Units
Sekitoshi Kanai, Yasuhiro Fujiwara, Sotetsu Iwamura
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander J Ratner, Henry Ehrenberg, Zeshan Hussain et al.
Learning Mixture of Gaussians with Streaming Data
Aditi Raghunathan, Prateek Jain, Ravishankar Krishnawamy
Optimal Shrinkage of Singular Values Under Random Data Contamination
Danny Barash, Matan Gavish
Deep Sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh et al.
Unsupervised Sequence Classification using Sequential Output Statistics
Yu Liu, Jianshu Chen, Li Deng
Learning Low-Dimensional Metrics
Blake Mason, Lalit Jain, Robert Nowak
Hash Embeddings for Efficient Word Representations
Dan Tito Svenstrup, Jonas Hansen, Ole Winther
Interactive Submodular Bandit
Lin Chen, Andreas Krause, Amin Karbasi
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson et al.
An inner-loop free solution to inverse problems using deep neural networks
Kai Fan, Qi Wei, Lawrence Carin et al.
Reconstructing perceived faces from brain activations with deep adversarial neural decoding
Yağmur Güçlütürk, Umut Güçlü, Katja Seeliger et al.
Estimating Mutual Information for Discrete-Continuous Mixtures
Weihao Gao, Sreeram Kannan, Sewoong Oh et al.
On the Model Shrinkage Effect of Gamma Process Edge Partition Models
Iku Ohama, Issei Sato, Takuya Kida et al.
Tensor Biclustering
Soheil Feizi, Hamid Javadi, David Tse
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski et al.
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J Maddison et al.
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
Rebecca Morrison, Ricardo Baptista, Youssef Marzouk
Adaptive Batch Size for Safe Policy Gradients
Matteo Papini, Matteo Pirotta, Marcello Restelli
Trimmed Density Ratio Estimation
Song Liu, Akiko Takeda, Taiji Suzuki et al.
Simple strategies for recovering inner products from coarsely quantized random projections
Ping Li, Martin Slawski
A Learning Error Analysis for Structured Prediction with Approximate Inference
Yuanbin Wu, Man Lan, Shiliang Sun et al.