Papers
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau et al.
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh, Razvan Pascanu, Samy Bengio et al.
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite, Anna Choromanska, David Sontag
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sliced Wasserstein Kernel for Persistence Diagrams
Mathieu Carrière, Marco Cuturi, Steve Oudot
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi, Mathieu Blondel
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
Pengfei Wei, Ramon Sagarna, Yiping Ke et al.
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang, Aurélie C. Lozano
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja Balle, Odalric-Ambrym Maillard
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Jun-ichiro Hirayama, Aapo Hyvärinen, Motoaki Kawanabe
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Juyong Kim, Yookoon Park, Gunhee Kim et al.
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster, Nantas Nardelli, Gregory Farquhar et al.
State-Frequency Memory Recurrent Neural Networks
Hao Hu, Guo-Jun Qi
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Tyler B. Johnson, Carlos Guestrin
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Chaoxu Zhou, Wenbo Gao, Donald Goldfarb
Stochastic Bouncy Particle Sampler
Ari Pakman, Dar Gilboa, David Carlson et al.
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Yi Xu, Qihang Lin, Tianbao Yang
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan et al.
Stochastic Generative Hashing
Bo Dai, Ruiqi Guo, Sanjiv Kumar et al.
Stochastic Gradient MCMC Methods for Hidden Markov Models
Yi-An Ma, Nicholas J. Foti, Emily B. Fox
Stochastic Gradient Monomial Gamma Sampler
Yizhe Zhang, Changyou Chen, Zhe Gan et al.
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms
Qianxiao Li, Cheng Tai, Weinan E
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li et al.