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ORCIDCHIL 2025: Stanford University, USA
- Beidi Chen, Shijia Liu, Mert Pilanci, Weijie Su, Jeremias Sulam, Yuxiang Wang, Zhihui Zhu:
Conference on Parsimony and Learning, Stanford University, USA, 24-27 March 2025. Proceedings of Machine Learning Research 280, PMLR 2025 - Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang:
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers. 1-23 - Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Junwei Yu:
Fast John Ellipsoid Computation with Differential Privacy Optimization. 24-64 - Jiaxin Hu:
Large-Scale Multiway Clustering with Seeded Clustering. 65-88 - Stanislas Ducotterd, Sebastian Neumayer, Michael Unser:
Learning of Patch-Based Smooth-Plus-Sparse Models for Image Reconstruction. 89-104 - Bo Chen, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song:
HSR-Enhanced Sparse Attention Acceleration. 105-133 - Ziwei Guan, Daouda Sow, Sen Lin, Yingbin Liang:
AdaProx: A Novel Method for Bilevel Optimization under Pessimistic Framework. 134-164 - Uday Singh Saini, William Shiao, Yahya Sattar, Yogesh Dahiya, Samet Oymak, Evangelos E. Papalexakis:
A Case Study of Low Ranked Self-Expressive Structures in Neural Network Representations. 165-236 - Huiwen Wu, Shuo Zhang:
Do Global and Local Perform Cooperatively or Adversarially in Heterogeneous Federated Learning? 237-254 - Hang Wang, Qiaoyi Fang, Junshan Zhang:
Heterogeneous Decision Making in Mixed Traffic: Uncertainty-aware Planning and Bounded Rationality. 255-277 - Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar:
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism. 278-304 - Abulikemu Abuduweili, Changliu Liu:
Revisiting the Initial Steps in Adaptive Gradient Descent Optimization. 305-322 - Lijun Ding, Zhen Qin, Liwei Jiang, Jinxin Zhou, Zhihui Zhu:
A Validation Approach to Over-parameterized Matrix and Image Recovery. 323-350 - Guangyi Liu, Yongqi Zhang, Yong Li, Quanming Yao:
Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering. 351-372 - Suman Sapkota, Binod Bhattarai:
Dimension Mixer: Group Mixing of Input Dimensions for Efficient Function Approximation. 373-391 - Fangshuo Liao, Wenyi Su, Anastasios Kyrillidis:
Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation. 392-416 - Junjie Yang, Jinze Zhao, Peihao Wang, Zhangyang Wang, Yingbin Liang:
Meta ControlNet: Enhancing Task Adaptation via Meta Learning. 417-432 - Zhenzhen Wang, Aleksander S. Popel, Jeremias Sulam:
Concept Bottleneck Model with Zero Performance Loss. 433-461 - Nurbek Tastan, Samuel Horváth, Martin Takác, Karthik Nandakumar:
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning. 462-483 - Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder:
A unified framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. 484-499 - Jianwei Li, Yijun Dong, Qi Lei:
Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining. 500-520 - Esha Singh, Shoham Sabach, Yu-Xiang Wang:
MoXCo: How I learned to stop exploring and love my local minima? 521-544 - Majid Daliri, Zhao Song, Chiwun Yang:
Unlock the Theory behind Scaling 1-bit Neural Networks. 545-598 - Tao Wen, Elynn Y. Chen, Yuzhou Chen, Qi Lei:
Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation. 599-614 - Albert Dorador:
Theoretical and Empirical Advances in Forest Pruning. 615-651 - Sean Plummer, Anirban Bhattacharya, Debdeep Pati, Yun Yang:
Asymptotic Behavior of the Coordinate Ascent Variational Inference in Singular Models. 652-674 - Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang:
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond. 675-738 - Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song:
The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity. 739-767 - Ruinan Wang, Ian T. Nabney, Mohammad Golbabaee:
Grouped Sequential Optimization Strategy - the Application of Hyperparameter Importance Assessment in Deep Learning. 768-779 - Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu:
You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Time. 780-809 - Hao Bai, Yi Ma:
Improving Neuron-level Interpretability with White-box Language Models. 810-836 - David A. Quiroga, Jason Han, Anastasios Kyrillidis:
Quantum EigenGame for excited state calculation. 837-864 - Mathias Schmolli, Maximilian Baronig, Robert Legenstein, Ozan Özdenizci:
Adversarially Robust Spiking Neural Networks with Sparse Connectivity. 865-883 - Dongwei Wang, Huanrui Yang:
Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization. 884-896 - Tom Pan, Evan Dramko, Mitchell D. Miller, George N. Phillips Jr., Anastasios Kyrillidis:
RecCrysFormer: Refined Protein Structural Prediction from 3D Patterson Maps via Recycling Training Runs. 897-912 - Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos:
Learning Effective Dynamics across Spatio-Temporal Scales of Complex Flows. 913-931 - Zhao Song, Weixin Wang, Chenbo Yin, Junze Yin:
Fast and Efficient Matching Algorithm with Deadline Instances. 932-959 - Jan-Philipp von Bassewitz, Sebastian Kaltenbach, Petros Koumoutsakos:
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning. 960-984 - Xue Feng, M. Paul Laiu, Thomas Strohmer:
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration. 985-1006 - Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu:
Enhancing Video Representation Learning with Temporal Differentiation. 1007-1034 - Zhenyu Zhang, Ajay Kumar Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. 1035-1050 - Xingyu Qu, Samuel Horváth:
Vanishing Feature: Diagnosing Model Merging and Beyond. 1051-1086 - Wei Huang, Wuyang Chen, Zhiqiang Xu, Zhangyang Wang, Taiji Suzuki:
Exact and Rich Feature Learning Dynamics of Two-Layer Linear Networks. 1087-1111 - Jie Peng, Sukwon Yun, Kaixiong Zhou, Ruida Zhou, Thomas Hartvigsen, Yanyong Zhang, Zhangyang Wang, Tianlong Chen:
Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning. 1112-1145 - Siyi Liu, Chen Gao, Yong Li:
AgentHPO: Large Language Model Agent for Hyper-Parameter Optimization. 1146-1169 - Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna:
Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers. 1170-1190 - Beepul Bharti, Paul H. Yi, Jeremias Sulam:
Sufficient and Necessary Explanations (and What Lies in Between). 1191-1215 - Yichuan Deng, Jiangxuan Long, Zhao Song, Zifan Wang, Han Zhang:
Streaming Kernel PCA Algorithm With Small Space. 1216-1254 - Arthur Jacot, Alexandre Kaiser:
Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets. 1255-1273 - William T. Redman, Zhangyang Wang, Alessandro Ingrosso, Sebastian Goldt:
How Iterative Magnitude Pruning Discovers Local Receptive Fields in Fully Connected Neural Networks. 1274-1291 - Ziyan Zheng, Chin Wa Lau, Nian Guo, Xiang Shi, Shao-Lun Huang:
White-box Error Correction Code Transformer. 1292-1306 - Jinxin Zhou, Jiachen Jiang, Zhihui Zhu:
Are all layers created equal: A neural collapse perspective. 1307-1327 - Abdulla Jasem Almansoori, Samuel Horváth, Martin Takác:
Collaborative and Efficient Personalization with Mixtures of Adaptors. 1328-1364 - Can Yaras, Siyi Chen, Peng Wang, Qing Qu:
Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning. 1365-1387 - Tomer Galanti, Zachary S. Siegel, Aparna Gupte, Tomaso A. Poggio:
SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks. 1388-1412 - Shijin Duan, Yejia Liu, Gaowen Liu, Ramana Rao Kompella, Shaolei Ren, Xiaolin Xu:
Towards Vector Optimization on Low-Dimensional Vector Symbolic Architecture. 1413-1432
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last updated on 2025-11-17 22:50 CET by the dblp team
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