Papers
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit K Jain et al.
Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
Rohan Ghuge, Vidya Muthukumar, Sahil Singla
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi et al.
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions
Supratim Shit, Gurmehak Kaur Chadha, Surendra Kumar et al.
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen et al.
Improved Expressivity of Hypergraph Neural Networks through High-Dimensional Generalized Weisfeiler-Leman Algorithms
Detian Zhang, Chengqiang Zhang, Yanghui Rao et al.
Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
Zijian Liu, Zhengyuan Zhou
Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivošija, Alexander Munteanu, André Nusser et al.
Improved Off-policy Reinforcement Learning in Biological Sequence Design
Hyeonah Kim, Minsu Kim, Taeyoung Yun et al.
Improved Online Confidence Bounds for Multinomial Logistic Bandits
Joongkyu Lee, Min-Hwan Oh
Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
Guy Kornowski, Daogao Liu, Kunal Talwar
Improving Compositional Generation with Diffusion Models Using Lift Scores
Chenning Yu, Sicun Gao
Improving Consistency Models with Generator-Augmented Flows
Thibaut Issenhuth, Sangchul Lee, Ludovic Dos Santos et al.
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng et al.
Improving Flow Matching by Aligning Flow Divergence
Yuhao Huang, Taos Transue, Shih-Hsin Wang et al.
Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging
Junkang Liu, Yuanyuan Liu, Fanhua Shang et al.
Improving Generalization with Flat Hilbert Bayesian Inference
Tuan Truong, Quyen Tran, Ngoc-Quan Pham et al.
Improving LLM Safety Alignment with Dual-Objective Optimization
Xuandong Zhao, Will Cai, Tianneng Shi et al.
Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens
Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen et al.
Improving LLM Video Understanding with 16 Frames Per Second
Yixuan Li, Changli Tang, Jimin Zhuang et al.
Improving Memory Efficiency for Training KANs via Meta Learning
Zhangchi Zhao, Jun Shu, Deyu Meng et al.