Papers
A Modern Self-Referential Weight Matrix That Learns to Modify Itself
Kazuki Irie, Imanol Schlag, Róbert Csordás et al.
A Multi-objective / Multi-task Learning Framework Induced by Pareto Stationarity
Michinari Momma, Chaosheng Dong, Jia Liu
Analysis of Stochastic Processes through Replay Buffers
Shirli Di-Castro, Shie Mannor, Dotan Di Castro
Analyzing and Mitigating Interference in Neural Architecture Search
Jin Xu, Xu Tan, Kaitao Song et al.
An Analytical Update Rule for General Policy Optimization
Hepeng Li, Nicholas Clavette, Haibo He
Anarchic Federated Learning
Haibo Yang, Xin Zhang, Prashant Khanduri et al.
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings
Meyer Scetbon, Laurent Meunier, Yaniv Romano
A Natural Actor-Critic Framework for Zero-Sum Markov Games
Ahmet Alacaoglu, Luca Viano, Niao He et al.
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks
Sadegh Farhadkhani, Rachid Guerraoui, Lê Nguyên Hoang et al.
A Neural Tangent Kernel Perspective of GANs
Jean-Yves Franceschi, Emmanuel De Bézenac, Ibrahim Ayed et al.
A New Perspective on the Effects of Spectrum in Graph Neural Networks
Mingqi Yang, Yanming Shen, Rui Li et al.
A new similarity measure for covariate shift with applications to nonparametric regression
Reese Pathak, Cong Ma, Martin Wainwright
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming
Jihwan Jeong, Parth Jaggi, Andrew Butler et al.
An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hazla et al.
An Intriguing Property of Geophysics Inversion
Yinan Feng, Yinpeng Chen, Shihang Feng et al.
An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees
Guillaume Braun, Hemant Tyagi, Christophe Biernacki
Antibody-Antigen Docking and Design via Hierarchical Structure Refinement
Wengong Jin, Dr.Regina Barzilay, Tommi Jaakkola
Anticorrelated Noise Injection for Improved Generalization
Antonio Orvieto, Hans Kersting, Frank Proske et al.
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology
Brandon Trabucco, Mariano Phielipp, Glen Berseth
Anytime Information Cascade Popularity Prediction via Self-Exciting Processes
Xi Zhang, Akshay Aravamudan, Georgios C Anagnostopoulos
A Parametric Class of Approximate Gradient Updates for Policy Optimization
Ramki Gummadi, Saurabh Kumar, Junfeng Wen et al.
Approximate Bayesian Computation with Domain Expert in the Loop
Ayush Bharti, Louis Filstroff, Samuel Kaski
Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets
Baojian Zhou, Yifan Sun
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
Rui Wang, Robin Walters, Rose Yu
A Psychological Theory of Explainability
Scott Cheng-Hsin Yang, Nils Erik Tomas Folke, Patrick Shafto