Papers
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz, Jiri Hron, Przemysław Mazur et al.
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia et al.
Superposition of many models into one
Brian Cheung, Alexander Terekhov, Yubei Chen et al.
Superset Technique for Approximate Recovery in One-Bit Compressed Sensing
Larkin Flodin, Venkata Gandikota, Arya Mazumdar
Surfing: Iterative Optimization Over Incrementally Trained Deep Networks
Ganlin Song, Zhou Fan, John Lafferty
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making
Minmin Chen, Ramki Gummadi, Chris Harris et al.
Surround Modulation: A Bio-inspired Connectivity Structure for Convolutional Neural Networks
Hosein Hasani, Mahdieh Soleymani, Hamid Aghajan
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas Gebauer, Michael Gastegger, Kristof Schütt
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments
Hugo Caselles-Dupré, Michael Garcia Ortiz, David Filliat
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Nikolas Ioannou, Celestine Mendler-Dünner, Thomas Parnell
TAB-VCR: Tags and Attributes based VCR Baselines
Jingxiang Lin, Unnat Jain, Alexander Schwing
Teaching Multiple Concepts to a Forgetful Learner
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha et al.
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations.
Sawyer Birnbaum, Volodymyr Kuleshov, Zayd Enam et al.
Tensor Monte Carlo: Particle Methods for the GPU era
Laurence Aitchison
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning
Ruiyi Zhang, Tong Yu, Yilin Shen et al.
The Broad Optimality of Profile Maximum Likelihood
Yi Hao, Alon Orlitsky
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data
Amanda Gentzel, Dan Garant, David Jensen
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
Alex Lu, Amy Lu, Wiebke Schormann et al.
The continuous Bernoulli: fixing a pervasive error in variational autoencoders
Gabriel Loaiza-Ganem, John P. Cunningham
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Basri Ronen, David Jacobs, Yoni Kasten et al.
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric
Nathan Kallus, Angela Zhou
The Functional Neural Process
Christos Louizos, Xiahan Shi, Klamer Schutte et al.
The Geometry of Deep Networks: Power Diagram Subdivision
Randall Balestriero, Romain Cosentino, Behnaam Aazhang et al.
The Impact of Regularization on High-dimensional Logistic Regression
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
The Implicit Bias of AdaGrad on Separable Data
Qian Qian, Xiaoyuan Qian