Papers
Submodular Maximization Through Barrier Functions
Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi et al.
Submodular Meta-Learning
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Sub-sampling for Efficient Non-Parametric Bandit Exploration
Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard
Succinct and Robust Multi-Agent Communication With Temporal Message Control
Sai Qian Zhang, Qi Zhang, Jieyu Lin
Sufficient dimension reduction for classification using principal optimal transport direction
Cheng Meng, Jun Yu, Jingyi Zhang et al.
SuperLoss: A Generic Loss for Robust Curriculum Learning
Thibault Castells, Philippe Weinzaepfel, Jerome Revaud
Supermasks in Superposition
Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu et al.
Supervised Contrastive Learning
Prannay Khosla, Piotr Teterwak, Chen Wang et al.
SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm
Yi Hao, Ayush Jain, Alon Orlitsky et al.
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom et al.
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Sinho Chewi, Thibaut Le Gouic, Chen Lu et al.
Swapping Autoencoder for Deep Image Manipulation
Taesung Park, Jun-Yan Zhu, Oliver Wang et al.
Synbols: Probing Learning Algorithms with Synthetic Datasets
Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron et al.
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
Kavi Gupta, Peter Ebert Christensen, Xinyun Chen et al.
Synthesizing Tasks for Block-based Programming
Umair Ahmed, Maria Christakis, Aleksandr Efremov et al.
Synthetic Data Generators -- Sequential and Private
Olivier Bousquet, Roi Livni, Shay Moran
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
Cornelius Schröder, David Klindt, Sarah Strauss et al.
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Jianyu Wang, Qinghua Liu, Hao Liang et al.
Taming Discrete Integration via the Boon of Dimensionality
Jeffrey Dudek, Dror Fried, Kuldeep S Meel
Targeted Adversarial Perturbations for Monocular Depth Prediction
Alex Wong, Safa Cicek, Stefano Soatto
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters
Sulin Liu, Xingyuan Sun, Peter J. Ramadge et al.
Task-agnostic Exploration in Reinforcement Learning
Xuezhou Zhang, Yuzhe Ma, Adish Singla
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
Mengdi Xu, Wenhao Ding, Jiacheng Zhu et al.
Task-Oriented Feature Distillation
Linfeng Zhang, Yukang Shi, Zuoqiang Shi et al.
Task-Robust Model-Agnostic Meta-Learning
Liam Collins, Aryan Mokhtari, Sanjay Shakkottai