Papers
11,015 papers found
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
Brian Chmiel, Itay Hubara, Ron Banner et al.
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning
Alex Gu, Songtao Lu, Parikshit Ram et al.
Mitigating Dataset Bias by Using Per-Sample Gradient
Sumyeong Ahn, Seongyoon Kim, Se-Young Yun
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach
Heshan Devaka Fernando, Han Shen, Miao Liu et al.
Mitigating Memorization of Noisy Labels via Regularization between Representations
Hao Cheng, Zhaowei Zhu, Xing Sun et al.
MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer
Qihao Zhao, Yangyu Huang, Wei Hu et al.
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation
Junjie Yang, Xuxi Chen, Tianlong Chen et al.
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Xiaotian Han, Tong Zhao, Yozen Liu et al.
MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises
Emanuele Palumbo, Imant Daunhawer, Julia E Vogt
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
Chenglin Yang, Siyuan Qiao, Qihang Yu et al.
MocoSFL: enabling cross-client collaborative self-supervised learning
Jingtao Li, Lingjuan Lyu, Daisuke Iso et al.
Model-based Causal Bayesian Optimization
Scott Sussex, Anastasia Makarova, Andreas Krause
Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning
XIANGYU PENG, Chen Xing, Prafulla Kumar Choubey et al.
Modeling content creator incentives on algorithm-curated platforms
Jiri Hron, Karl Krauth, Michael Jordan et al.
Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts
Zhitong Gao, Yucong Chen, Chuyu Zhang et al.
Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval
Shunyu Zhang, Yaobo Liang, MING GONG et al.
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN
David M Knigge, David W. Romero, Albert Gu et al.
MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations
Nicklas Hansen, Yixin Lin, Hao Su et al.
Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning
Xiaobo Xia, Jiale Liu, Jun Yu et al.
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
Jun Xia, Chengshuai Zhao, Bozhen Hu et al.
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching
Shengchao Liu, Hongyu Guo, Jian Tang
Molecule Generation For Target Protein Binding with Structural Motifs
ZAIXI ZHANG, Yaosen Min, Shuxin Zheng et al.
Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport
Lingkai Kong, Yuqing Wang, Molei Tao
Monocular Scene Reconstruction with 3D SDF Transformers
Weihao Yuan, Xiaodong Gu, Heng Li et al.