Papers
Spectral Pruning for Recurrent Neural Networks
Takashi Furuya, Kazuma Suetake, Koichi Taniguchi et al.
Spectral risk-based learning using unbounded losses
Matthew J. Holland, El Mehdi Haress
Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models
Flavio Chierichetti, Alessandro Panconesi, Giuseppe Re et al.
Spiked Covariance Estimation from Modulo-Reduced Measurements
Elad Romanov, Or Ordentlich
State Dependent Performative Prediction with Stochastic Approximation
Qiang Li, Hoi-To Wai
Stateful Offline Contextual Policy Evaluation and Learning
Nathan Kallus, Angela Zhou
Statistical and computational thresholds for the planted k-densest sub-hypergraph problem
Luca Corinzia, Paolo Penna, Wojciech Szpankowski et al.
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications
Morgane Goibert, Stephan Clemencon, Ekhine Irurozki et al.
Stochastic Extragradient: General Analysis and Improved Rates
Eduard Gorbunov, Hugo Berard, Gauthier Gidel et al.
Strategic ranking
Lydia T. Liu, Nikhil Garg, Christian Borgs
Structured Multi-task Learning for Molecular Property Prediction
Shengchao Liu, Meng Qu, Zuobai Zhang et al.
Structured variational inference in Bayesian state-space models
Honggang Wang, Anirban Bhattacharya, Debdeep Pati et al.
Super-Acceleration with Cyclical Step-sizes
Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut et al.
Survival regression with proper scoring rules and monotonic neural networks
David Rindt, Robert Hu, David Steinsaltz et al.
Synthsonic: Fast, Probabilistic modeling and Synthesis of Tabular Data
Max Baak, Simon Brugman, Ilan Fridman Rojas et al.
TD-GEN: Graph Generation Using Tree Decomposition
Hamed Shirzad, Hossein Hajimirsadeghi, Amir H. Abdi et al.
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
Lenon Minorics, Caner Turkmen, David Kernert et al.
The Curse of Passive Data Collection in Batch Reinforcement Learning
Chenjun Xiao, Ilbin Lee, Bo Dai et al.
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?
Robin Vandaele, Bo Kang, Tijl De Bie et al.
The Fast Kernel Transform
John P. Ryan, Sebastian E. Ament, Carla P. Gomes et al.
The Importance of Future Information in Credit Card Fraud Detection
Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer et al.
The role of optimization geometry in single neuron learning
Nicholas Boffi, Stephen Tu, Jean-Jacques Slotine
The Tree Loss: Improving Generalization with Many Classes
Yujie Wang, Mike Izbicki