Optimization & Theory

Deep Equilibrium Models for Snapshot Compressive Imaging AAAI 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Deep linear networks can benignly overfit when shallow ones do JMLR 2023 DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network CVPR 2023 DeepPCR: Parallelizing Sequential Operations in Neural Networks NeurIPS 2023 Deep Random Projector: Accelerated Deep Image Prior CVPR 2023 Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time ICML 2023 Delay-penalized CTC Implemented Based on Finite State Transducer Interspeech 2023 Demystifying Oversmoothing in Attention-Based Graph Neural Networks NeurIPS 2023 Demystifying Prompts in Language Models via Perplexity Estimation EMNLP 2023 DepGraph: Towards Any Structural Pruning CVPR 2023 Detecting and Repairing Deviated Outputs of Compressed Models ACML 2023 DiFA: Differentiable Feature Acquisition AAAI 2023 Differentiable Architecture Search With Random Features CVPR 2023 Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick NeurIPS 2023 Differentiable Shadow Mapping for Efficient Inverse Graphics CVPR 2023 Differentially Private Learning with Per-Sample Adaptive Clipping AAAI 2023 DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-efficient Fine-Tuning ICCV 2023 Diffuser: Efficient Transformers with Multi-Hop Attention Diffusion for Long Sequences AAAI 2023 Diffusion Models are Minimax Optimal Distribution Estimators ICML 2023 Diffusion Models Beat GANs on Topology Optimization AAAI 2023 Digital Typhoon: Long-term Satellite Image Dataset for the Spatio-Temporal Modeling of Tropical Cyclones NeurIPS 2023 Dimensionality-Varying Diffusion Process CVPR 2023 DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training CVPR 2023 Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models ICML 2023