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Optimization & Theory

7,804 papers (27 classified directly here)

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1,352
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Papers (including subtopics)

On the Dynamics Under the Unhinged Loss and Beyond JMLR 2023 On the Evaluation of Neural Selective Prediction Methods for Natural Language Processing ACL 2023 On the Expressive Flexibility of Self-Attention Matrices AAAI 2023 On the Expressivity Role of LayerNorm in Transformers’ Attention ACL 2023 On the impact of activation and normalization in obtaining isometric embeddings at initialization NeurIPS 2023 On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data AISTATS 2023 On the Initialization of Graph Neural Networks ICML 2023 On the Stability and Generalization of Triplet Learning AAAI 2023 On the Training Instability of Shuffling SGD with Batch Normalization ICML 2023 OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data AAAI 2023 Optimal Convergence Rates for Agnostic Nyström Kernel Learning ICML 2023 Optimal Nonlinearities Improve Generalization Performance of Random Features ACML 2023 Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection NeurIPS 2023 Optimal Sets and Solution Paths of ReLU Networks ICML 2023 Optimal Shrinkage for Distributed Second-Order Optimization ICML 2023 Optimizing Mode Connectivity for Class Incremental Learning ICML 2023 Oscillation-free Quantization for Low-bit Vision Transformers ICML 2023 Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling EMNLP 2023 Overcoming Forgetting Catastrophe in Quantization-Aware Training ICCV 2023 Overparameterized Random Feature Regression with Nearly Orthogonal Data AISTATS 2023 PAD-Net: An Efficient Framework for Dynamic Networks ACL 2023 Parameter-Efficient Fine-Tuning without Introducing New Latency ACL 2023 Parameter Efficient Local Implicit Image Function Network for Face Segmentation CVPR 2023 Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck NeurIPS 2023 Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis ICCV 2023