Optimization

DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models CVPR 2024 DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models ICML 2024 DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization NeurIPS 2024 Directional Optimism for Safe Linear Bandits AISTATS 2024 Directional Smoothness and Gradient Methods: Convergence and Adaptivity NeurIPS 2024 Directly Fine-Tuning Diffusion Models on Differentiable Rewards ICLR 2024 Direct Multi-Turn Preference Optimization for Language Agents EMNLP 2024 Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits NeurIPS 2024 Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation MLHC 2024 Direct Preference Optimization with an Offset ACL 2024 Dirichlet Flow Matching with Applications to DNA Sequence Design ICML 2024 Discounted Adaptive Online Learning: Towards Better Regularization ICML 2024 Discovering Preference Optimization Algorithms with and for Large Language Models NeurIPS 2024 Discovering Sequential Patterns with Predictable Inter-event Delays AAAI 2024 Discriminator Guidance for Autoregressive Diffusion Models AISTATS 2024 Disperse-Then-Merge: Pushing the Limits of Instruction Tuning via Alignment Tax Reduction ACL 2024 Dissimilarity Bandits AISTATS 2024 Distance-Aware Non-IID Federated Learning for Generalization and Personalization in Medical Imaging Segmentation MIDL 2024 Distilling Autoregressive Models to Obtain High-Performance Non-autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed AAAI 2024 DistiLLM: Towards Streamlined Distillation for Large Language Models ICML 2024 DistillSpec: Improving Speculative Decoding via Knowledge Distillation ICLR 2024 Distributed Bilevel Optimization with Communication Compression ICML 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Distributed on-the-fly control of multi-agent systems with unknown dynamics: Using limited data to obtain near-optimal control L4DC 2024 Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024