Papers
938 papers found
Risk-limiting financial audits via weighted sampling without replacement
Shubhanshu Shekhar, Ziyu Xu, Zachary Lipton et al.
Robust distillation for worst-class performance: on the interplay between teacher and student objectives
Serena Wang, Harikrishna Narasimhan, Yichen Zhou et al.
Robust Gaussian process regression with the trimmed marginal likelihood
Daniel Andrade, Akiko Takeda
Robust Quickest Change Detection for Unnormalized Models
Suya Wu, Enmao Diao, Jie Ding et al.
Robust statistical comparison of random variables with locally varying scale of measurement
Christoph Jansen, Georg Schollmeyer, Hannah Blocher et al.
Sample Boosting Algorithm (SamBA) - An interpretable greedy ensemble classifier based on local expertise for fat data
Baptiste Bauvin, Cécile Capponi, Florence Clerc et al.
Scalable and robust tensor ring decomposition for large-scale data
Yicong He, George K. Atia
Scalable nonparametric Bayesian learning for dynamic velocity fields
Sunrit Chakraborty, Aritra Guha, Rayleigh Lei et al.
Scaling integer arithmetic in probabilistic programs
William X. Cao, Poorva Garg, Ryan Tjoa et al.
Semi-supervised learning of partial differential operators and dynamical flows
Michael Rotman, Amit Dekel, Ran Ilan Ber et al.
Simple Transferability Estimation for Regression Tasks
Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho et al.
Size-constrained k-submodular maximization in near-linear time
Guanyu Nie, Yanhui Zhu, Yididiya Y. Nadew et al.
Solving multi-model MDPs by coordinate ascent and dynamic programming
Xihong Su, Marek Petrik
SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models
Vithursan Thangarasa, Abhay Gupta, William Marshall et al.
Split, count, and share: a differentially private set intersection cardinality estimation protocol
Michael Purcell, Yang Li, Kee Siong Ng
Stochastic Generative Flow Networks
Ling Pan, Dinghuai Zhang, Moksh Jain et al.
Stochastic Graphical Bandits with Heavy-Tailed Rewards
Yutian Gou, Jinfeng Yi, Lijun Zhang
Structure-aware robustness certificates for graph classification
Pierre Osselin, Henry Kenlay, Xiaowen Dong
Studying the Effect of GNN Spatial Convolutions On The Embedding Space’s Geometry
Claire Donnat, So Won Jeong
SubMix: Learning to Mix Graph Sampling Heuristics
Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi et al.
Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms
Anna Guo, Jiwei Zhao, Razieh Nabi
SymNet 3.0: Exploiting Long-Range Influences in Learning Generalized Neural Policies for Relational MDPs
Vishal Sharma, Daman Arora, Mausam et al.
TCE: A Test-Based Approach to Measuring Calibration Error
Takuo Matsubara, Niek Tax, Richard Mudd et al.
Testing conventional wisdom (of the crowd)
Noah Burrell, Grant Schoenebeck
The past does matter: correlation of subsequent states in trajectory predictions of Gaussian Process models
Steffen Ridderbusch, Sina Ober-Blöbaum, Paul Goulart