Papers
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
Peng Jiang, Gagan Agrawal
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz, Leonid Karlinsky, Joseph Shtok et al.
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
Haoye Dong, Xiaodan Liang, Ke Gong et al.
SNIPER: Efficient Multi-Scale Training
Bharat Singh, Mahyar Najibi, Larry S. Davis
Heterogeneous Multi-output Gaussian Process Prediction
Pablo Moreno-Muñoz, Antonio Artés, Mauricio Álvarez
Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
Pavel Dvurechenskii, Darina Dvinskikh, Alexander Gasnikov et al.
Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data
Xenia Miscouridou, Francois Caron, Yee Whye Teh
Recurrently Controlled Recurrent Networks
Yi Tay, Anh Tuan Luu, Siu Cheung Hui
Dual Policy Iteration
Wen Sun, Geoffrey J. Gordon, Byron Boots et al.
Generalized Zero-Shot Learning with Deep Calibration Network
Shichen Liu, Mingsheng Long, Jianmin Wang et al.
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
Cong Fang, Chris Junchi Li, Zhouchen Lin et al.
Wasserstein Distributionally Robust Kalman Filtering
Soroosh Shafieezadeh-Abadeh, Viet Anh Nguyen, Daniel Huhn et al.
Scalable Hyperparameter Transfer Learning
Valerio Perrone, Rodolphe Jenatton, Matthias W Seeger et al.
Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres
Oisín Moran, Piergiorgio Caramazza, Daniele Faccio et al.
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma, Jie Chen, Cao Xiao
CatBoost: unbiased boosting with categorical features
Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev et al.
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Sham M. Kakade, Jason Lee
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization
Jie Cao, Yibo Hu, Hongwen Zhang et al.
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN
Shupeng Su, Chao Zhang, Kai Han et al.
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
Di Wang, Marco Gaboardi, Jinhui Xu
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
Constantinos Daskalakis, Ioannis Panageas
On Markov Chain Gradient Descent
Tao Sun, Yuejiao Sun, Wotao Yin
Stochastic Nested Variance Reduction for Nonconvex Optimization
Dongruo Zhou, Pan Xu, Quanquan Gu
Bayesian Inference of Temporal Task Specifications from Demonstrations
Ankit Shah, Pritish Kamath, Julie A Shah et al.