Papers
Off-policy Predictive Control with Causal Sensitivity Analysis
Myrl G Marmarelis, Ali Hasan, Kamyar Azizzadenesheli et al.
MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
Arto Maranjyan, Omar Shaikh Omar, Peter Richtárik
Testing Generalizability in Causal Inference
Daniel de Vassimon Manela, Linying Yang, Robin J. Evans
SALSA: A Secure, Adaptive and Label-Agnostic Scalable Algorithm for Machine Unlearning
Owais Makroo, Atif Hassan, Swanand Khare
Weak to Strong Learning from Aggregate Labels
Yukti Makhija, Rishi Saket
Multi-armed Bandits with Missing Outcomes
Ilia Mahrooghi, Mahshad Moradi, Sina Akbari et al.
Federated Rényi Fair Inference in Federated Heterogeneous System
Zhiyong Ma, Yuanjie Shi, Yan Yan et al.
Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold
Song Liu, Leyang Wang, Yakun Wang
Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection
Tianci Liu, Tong Yang, Quan Zhang et al.
Periodical Moving Average Accelerates Gradient Accumulation for Post-Training
Yumou Liu, An Li, Chaojie Li et al.
STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning
Zhuqing Liu, Chaosheng Dong, Michinari Momma et al.
Letting Uncertainty Guide Your Multimodal Machine Translation
Wuyi Liu, Yue Gao, Yige Mao et al.
DyGMAE: A Novel Dynamic Graph Masked Autoencoder for Link Prediction
Weixiong Liu, Junwei Cheng, Zhongyu Pan et al.
Multi-group Uncertainty Quantification for Long-form Text Generation
Terrance Liu, Steven Wu
CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization
Putri A Van der Linden, Alexander Timans, Erik J Bekkers
FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learning
I-Cheng Lin, Osman Yagan, Carlee Joe-Wong
Flat Posterior Does Matter For Bayesian Model Averaging
Sungjun Lim, Jeyoon Yeom, Sooyon Kim et al.
Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory
Jiehao Liang, Zhao Song, Zhaozhuo Xu et al.
Enhancing Uncertainty Quantification in Large Language Models through Semantic Graph Density
Zhaoye Li, Siyuan Shen, Wenjing Yang et al.
Trading Off Voting Axioms for Privacy
Zhechen Li, Ao Liu, Lirong Xia et al.
Constraint-based Causal Discovery from a Collection of Conditioning Sets
Kenneth Lee, Bruno Ribeiro, Murat Kocaoglu
Adaptive Reward Design for Reinforcement Learning
Minjae Kwon, Ingy ElSayed-Aly, Lu Feng
A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction
Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani et al.
Beyond Sin-Squared Error: Linear Time Entrywise Uncertainty Quantification for Streaming PCA
Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar
Budget Allocation Exploiting Label Correlation between Instances
Adithya Kulkarni, Mohna Chakraborty, Sihong Xie et al.