Papers
4,025 papers found
SoundSynp: Sound Source Detection from Raw Waveforms with Multi-Scale Synperiodic Filterbanks
Yuhang He, Andrew Markham
Sparse Bayesian optimization
Sulin Liu, Qing Feng, David Eriksson et al.
Sparse Spectral Bayesian Permanental Process with Generalized Kernel
Jeremy Sellier, Petros Dellaportas
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck
Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash et al.
Spectral Augmentations for Graph Contrastive Learning
Amur Ghose, Yingxue Zhang, Jianye Hao et al.
Spread Flows for Manifold Modelling
Mingtian Zhang, Yitong Sun, Chen Zhang et al.
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits
Wonyoung Kim, Myunghee Cho Paik, Min-Hwan Oh
Statistical Analysis of Karcher Means for Random Restricted PSD Matrices
Hengchao Chen, Xiang Li, Qiang Sun
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard et al.
Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints
Yao Yao, Qihang Lin, Tianbao Yang
Stochastic Mirror Descent for Large-Scale Sparse Recovery
Sasila Ilandarideva, Yannis Bekri, Anatoli Iouditski et al.
Stochastic Optimization for Spectral Risk Measures
Ronak Mehta, Vincent Roulet, Krishna Pillutla et al.
Stochastic Tree Ensembles for Estimating Heterogeneous Effects
Nikolay Krantsevich, Jingyu He, P. Richard Hahn
Strong Lottery Ticket Hypothesis with $\varepsilon$–perturbation
Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis
Structure of Nonlinear Node Embeddings in Stochastic Block Models
Christopher Harker, Aditya Bhaskara
Subset verification and search algorithms for causal DAGs
Davin Choo, Kirankumar Shiragur
Surveillance Evasion Through Bayesian Reinforcement Learning
Dongping Qi, David Bindel, Alexander Vladimirsky
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie et al.
Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence
Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang et al.
Temporal Graph Neural Networks for Irregular Data
Joel Oskarsson, Per Sidén, Fredrik Lindsten
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data
Frederiek Wesel, Kim Batselier
Testing of Horn Samplers
Ansuman Banerjee, Shayak Chakraborty, Sourav Chakraborty et al.
The communication cost of security and privacy in federated frequency estimation
Wei-Ning Chen, Ayfer Ozgur, Graham Cormode et al.