Papers
Support vector machines and linear regression coincide with very high-dimensional features
Navid Ardeshir, Clayton Sanford, Daniel J. Hsu
Surrogate Regret Bounds for Polyhedral Losses
Rafael M. Frongillo, Bo Waggoner
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
Alicia Curth, Changhee Lee, Mihaela van der Schaar
SWAD: Domain Generalization by Seeking Flat Minima
Junbum Cha, Sanghyuk Chun, Kyungjae Lee et al.
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding
Terrell Mundhenk, Mikel Landajuela, Ruben Glatt et al.
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
Irina Higgins, Peter Wirnsberger, Andrew Jaegle et al.
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory
Takashi Matsubara, Yuto Miyatake, Takaharu Yaguchi
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes
Zhaozhi Qian, Yao Zhang, Ioana Bica et al.
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls
Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie et al.
Systematic Generalization with Edge Transformers
Leon Bergen, Timothy O'Donnell, Dzmitry Bahdanau
TAAC: Temporally Abstract Actor-Critic for Continuous Control
Haonan Yu, Wei Xu, Haichao Zhang
Tactical Optimism and Pessimism for Deep Reinforcement Learning
Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano et al.
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
Minchao Wu, Michael Norrish, Christian Walder et al.
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time
Ferran Alet, Maria Bauza, Kenji Kawaguchi et al.
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning
Xin Zhang, Zhuqing Liu, Jia Liu et al.
Targeted Neural Dynamical Modeling
Cole Hurwitz, Akash Srivastava, Kai Xu et al.
Task-Adaptive Neural Network Search with Meta-Contrastive Learning
Wonyong Jeong, Hayeon Lee, Geon Park et al.
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data
Dongmin Park, Hwanjun Song, Minseok Kim et al.
Taxonomizing local versus global structure in neural network loss landscapes
Yaoqing Yang, Liam Hodgkinson, Ryan Theisen et al.
Teachable Reinforcement Learning via Advice Distillation
Olivia Watkins, Abhishek Gupta, Trevor Darrell et al.
Teaching an Active Learner with Contrastive Examples
Chaoqi Wang, Adish Singla, Yuxin Chen
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm
Akash Kumar, Yuxin Chen, Adish Singla
Techniques for Symbol Grounding with SATNet
Sever Topan, David Rolnick, Xujie Si
Temporal-attentive Covariance Pooling Networks for Video Recognition
Zilin Gao, Qilong Wang, Bingbing Zhang et al.
Temporally Abstract Partial Models
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici et al.