Papers
SLAYER: Spike Layer Error Reassignment in Time
Sumit Bam Shrestha, Garrick Orchard
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
Nima Anari, Constantinos Daskalakis, Wolfgang Maass et al.
Smoothed analysis of the low-rank approach for smooth semidefinite programs
Thomas Pumir, Samy Jelassi, Nicolas Boumal
Snap ML: A Hierarchical Framework for Machine Learning
Celestine Dünner, Thomas Parnell, Dimitrios Sarigiannis et al.
SNIPER: Efficient Multi-Scale Training
Bharat Singh, Mahyar Najibi, Larry S. Davis
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
Haoye Dong, Xiaodan Liang, Ke Gong et al.
Solving Large Sequential Games with the Excessive Gap Technique
Christian Kroer, Gabriele Farina, Tuomas Sandholm
Solving Non-smooth Constrained Programs with Lower Complexity than $\mathcal{O}(1/\varepsilon)$: A Primal-Dual Homotopy Smoothing Approach
Xiaohan Wei, Hao Yu, Qing Ling et al.
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Nan Rosemary Ke, Anirudh Goyal ALIAS PARTH GOYAL, Olexa Bilaniuk et al.
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo, Chao Zhang, Changshui Zhang et al.
Sparse PCA from Sparse Linear Regression
Guy Bresler, Sung Min Park, Madalina Persu
Sparsified SGD with Memory
Sebastian U Stich, Jean-Baptiste Cordonnier, Martin Jaggi
Speaker-Follower Models for Vision-and-Language Navigation
Daniel Fried, Ronghang Hu, Volkan Cirik et al.
Spectral Filtering for General Linear Dynamical Systems
Elad Hazan, Holden Lee, Karan Singh et al.
Spectral Signatures in Backdoor Attacks
Brandon Tran, Jerry Li, Aleksander Madry
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
Cong Fang, Chris Junchi Li, Zhouchen Lin et al.
SplineNets: Continuous Neural Decision Graphs
Cem Keskin, Shahram Izadi
Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
yunlong yu, Zhong Ji, Yanwei Fu et al.
Statistical and Computational Trade-Offs in Kernel K-Means
Daniele Calandriello, Lorenzo Rosasco
Statistical mechanics of low-rank tensor decomposition
Jonathan Kadmon, Surya Ganguli
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes
Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach
Stein Variational Gradient Descent as Moment Matching
Qiang Liu, Dilin Wang
Step Size Matters in Deep Learning
Kamil Nar, Shankar Sastry
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Fabian Sinz, Alexander S Ecker, Paul Fahey et al.
Stochastic Chebyshev Gradient Descent for Spectral Optimization
Insu Han, Haim Avron, Jinwoo Shin