Papers
Layer-wise Quantization for Quantized Optimistic Dual Averaging
Anh Duc Nguyen, Ilia Markov, Zhengqing Wu et al.
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
Li Ding, Hao Zhang, Wenrui Dai et al.
L-Diffusion: Laplace Diffusion for Efficient Pathology Image Segmentation
Weihan Li, Linyun Zhou, Jian Yang et al.
LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models
Jinho Chang, Jong Chul Ye
Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees
Thien Hang Nguyen, Huy Nguyen
LEAPS: A discrete neural sampler via locally equivariant networks
Peter Holderrieth, Michael Samuel Albergo, Tommi Jaakkola
Learnable Spatial-Temporal Positional Encoding for Link Prediction
Katherine Tieu, Dongqi Fu, Zihao Li et al.
Learn Beneficial Noise as Graph Augmentation
Siqi Huang, Yanchen Xu, Hongyuan Zhang et al.
Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi et al.
Learngene Tells You How to Customize: Task-Aware Parameter Initialization at Flexible Scales
Jiaze Xu, Shiyu Xia, Xu Yang et al.
Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang et al.
Learning Adversarial MDPs with Stochastic Hard Constraints
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning
Ngoc Bui, Menglin Yang, Runjin Chen et al.
Learning Attribute-Aware Hash Codes for Fine-Grained Image Retrieval via Query Optimization
Peng Wang, Yong Li, Lin Zhao et al.
Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors
Matei Gabriel Cosa, Marek Elias
Learning-Augmented Hierarchical Clustering
Vladimir Braverman, Jon C. Ergun, Chen Wang et al.
Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response
Kexin Huang, Ziqian Chen, Xue Wang et al.
Learning Cascade Ranking as One Network
Yunli Wang, Zhen Zhang, Zhiqiang Wang et al.
Learning Changes in Graphon Attachment Network Models
Xinyuan Fan, Bufan Li, Chenlei Leng et al.
Learning Classifiers That Induce Markets
Yonatan Sommer, Ivri Hikri, Lotan Amit et al.
Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
Jie Wen, Yadong Liu, Zhanyan Tang et al.
Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction
Ankit Ghosh, Gargee Kashyap, Sarthak Mittal et al.
Learning Configurations for Data-Driven Multi-Objective Optimization
Zhiyang Chen, Hailong Yao, Xia Yin
Learning Curves of Stochastic Gradient Descent in Kernel Regression
Haihan Zhang, Weicheng Lin, Yuanshi Liu et al.
Learning curves theory for hierarchically compositional data with power-law distributed features
Francesco Cagnetta, Hyunmo Kang, Matthieu Wyart