Papers
8,340 papers found
Improved Algorithms for White-Box Adversarial Streams
Ying Feng, David Woodruff
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions
Hongrui Chen, Holden Lee, Jianfeng Lu
Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis
Yongho Shin, Changyeol Lee, Gukryeol Lee et al.
Improved Online Conformal Prediction via Strongly Adaptive Online Learning
Aadyot Bhatnagar, Huan Wang, Caiming Xiong et al.
Improved Online Learning Algorithms for CTR Prediction in Ad Auctions
Zhe Feng, Christopher Liaw, Zixin Zhou
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
Aditya Mate, Bryan Wilder, Aparna Taneja et al.
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
Uri Sherman, Tomer Koren, Yishay Mansour
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
Kaiwen Zheng, Cheng Lu, Jianfei Chen et al.
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
Dongyoon Yang, Insung Kong, Yongdai Kim
Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics
Zonghan Yang, Peng Li, Tianyu Pang et al.
Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process
Yidong Ouyang, Liyan Xie, Guang Cheng
Improving Expert Predictions with Conformal Prediction
Eleni Straitouri, Lequn Wang, Nastaran Okati et al.
Improving Fair Training under Correlation Shifts
Yuji Roh, Kangwook Lee, Steven Euijong Whang et al.
Improving Graph Generation by Restricting Graph Bandwidth
Nathaniel Lee Diamant, Alex M Tseng, Kangway V. Chuang et al.
Improving Graph Neural Networks with Learnable Propagation Operators
Moshe Eliasof, Lars Ruthotto, Eran Treister
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
Rui Li, S. T. John, Arno Solin
Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints
Vaclav Voracek, Matthias Hein
Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling
Xinlu Zhang, Shiyang Li, Zhiyu Chen et al.
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models
Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich et al.
Improving the Model Consistency of Decentralized Federated Learning
Yifan Shi, Li Shen, Kang Wei et al.
Improving Visual Prompt Tuning for Self-supervised Vision Transformers
Seungryong Yoo, Eunji Kim, Dahuin Jung et al.
IncDSI: Incrementally Updatable Document Retrieval
Varsha Kishore, Chao Wan, Justin Lovelace et al.
Individually Fair Learning with One-Sided Feedback
Yahav Bechavod, Aaron Roth