{"url":"/method/adopt","slug":"adopt","name":"ADOPT","full_name":"ADaptive gradient method with the OPTimal convergence rate","full_name_withheld":false,"description_markdown":null,"description_state":"placeholder","introduced_year":null,"introduced_by":{"title":"ADOPT: Modified Adam Can Converge with Any $β_2$ with the Optimal Rate","paper":"/paper/adopt-modified-adam-can-converge-with-any-b-2","first_author":"Shohei Taniguchi","n_authors":10,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/adopt-modified-adam-can-converge-with-any-b-2"},"source":{"url":"https://arxiv.org/abs/2411.02853v3","title":"ADOPT: Modified Adam Can Converge with Any $β_2$ with the Optimal Rate","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Optimization","url":"/methods/category/optimization","pwc_aliases":[]},{"area":"General","area_id":"general","collection":"Stochastic Optimization","url":"/methods/category/stochastic-optimization","pwc_aliases":[]}],"n_papers_tagged":831,"archive_num_papers":832,"papers_newest_first":[{"paper":null,"title":"RegCL: Continual Adaptation of Segment Anything Model via Model Merging","date":"2025-07-16","arxiv_id":"2507.12297","n_code_links":0,"syntology":null},{"paper":null,"title":"Efficient Discovery of Actual Causality with Uncertainty","date":"2025-07-11","arxiv_id":"2507.09000","n_code_links":0,"syntology":null},{"paper":"/paper/fairness-is-not-enough-auditing-competence","title":"Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening","date":"2025-07-11","arxiv_id":"2507.11548","n_code_links":1,"syntology":null},{"paper":null,"title":"RAPS-3D: Efficient interactive segmentation for 3D radiological imaging","date":"2025-07-10","arxiv_id":"2507.07730","n_code_links":0,"syntology":null},{"paper":null,"title":"Integrated Structural Prompt Learning for Vision-Language Models","date":"2025-07-08","arxiv_id":"2507.05677","n_code_links":0,"syntology":null},{"paper":null,"title":"Unconditional Diffusion for Generative Sequential Recommendation","date":"2025-07-08","arxiv_id":"2507.06121","n_code_links":0,"syntology":null},{"paper":null,"title":"Kalman Filter Aided Federated Koopman Learning","date":"2025-07-07","arxiv_id":"2507.04808","n_code_links":0,"syntology":null},{"paper":null,"title":"Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model","date":"2025-07-07","arxiv_id":"2507.05513","n_code_links":0,"syntology":null},{"paper":"/paper/vote-vision-language-action-optimization-with","title":"VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting","date":"2025-07-07","arxiv_id":"2507.05116","n_code_links":1,"syntology":{"ran":0,"of":5,"unverified":5,"pointer_only":5}},{"paper":null,"title":"Advanced Financial Reasoning at Scale: A Comprehensive Evaluation of Large Language Models on CFA Level III","date":"2025-06-29","arxiv_id":"2507.02954","n_code_links":0,"syntology":null},{"paper":null,"title":"Potential Customer Lifetime Value in Financial Institutions: The Usage Of Open Banking Data to Improve CLV Estimation","date":"2025-06-28","arxiv_id":"2506.22711","n_code_links":0,"syntology":null},{"paper":"/paper/dbconformer-dual-branch-convolutional","title":"DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding","date":"2025-06-26","arxiv_id":"2506.21140","n_code_links":1,"syntology":null},{"paper":null,"title":"Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments","date":"2025-06-26","arxiv_id":"2506.21497","n_code_links":0,"syntology":null},{"paper":"/paper/kalm-embedding-v2-superior-training","title":"KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Model","date":"2025-06-26","arxiv_id":"2506.20923","n_code_links":1,"syntology":null},{"paper":null,"title":"Point Cloud Environment-Based Channel Knowledge Map Construction","date":"2025-06-26","arxiv_id":"2506.21112","n_code_links":0,"syntology":null},{"paper":null,"title":"YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection","date":"2025-06-26","arxiv_id":"2506.21135","n_code_links":0,"syntology":null},{"paper":null,"title":"Define-ML: An Approach to Ideate Machine Learning-Enabled Systems","date":"2025-06-25","arxiv_id":"2506.20621","n_code_links":0,"syntology":null},{"paper":null,"title":"Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images","date":"2025-06-25","arxiv_id":"2506.20407","n_code_links":0,"syntology":null},{"paper":null,"title":"Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning","date":"2025-06-25","arxiv_id":"2506.20651","n_code_links":0,"syntology":null},{"paper":null,"title":"Diffusion-based Task-oriented Semantic Communications with Model Inversion Attack","date":"2025-06-24","arxiv_id":"2506.19886","n_code_links":0,"syntology":null},{"paper":null,"title":"Finite-Horizon Strategy in Infinite-Horizon Linear-Quadratic Discrete-Time Dynamic Games","date":"2025-06-24","arxiv_id":"2506.19565","n_code_links":0,"syntology":null},{"paper":null,"title":"On the efficacy of old features for the detection of new bots","date":"2025-06-24","arxiv_id":"2506.19635","n_code_links":0,"syntology":null},{"paper":"/paper/open-vocabulary-camouflaged-object-1","title":"Open-Vocabulary Camouflaged Object Segmentation with Cascaded Vision Language Models","date":"2025-06-24","arxiv_id":"2506.19300","n_code_links":1,"syntology":null},{"paper":null,"title":"A Multi-Scale Spatial Attention-Based Zero-Shot Learning Framework for Low-Light Image Enhancement","date":"2025-06-23","arxiv_id":"2506.18323","n_code_links":0,"syntology":null},{"paper":"/paper/duetgen-music-driven-two-person-dance","title":"DuetGen: Music Driven Two-Person Dance Generation via Hierarchical Masked Modeling","date":"2025-06-23","arxiv_id":"2506.18680","n_code_links":1,"syntology":null},{"paper":null,"title":"Let Your Video Listen to Your Music!","date":"2025-06-23","arxiv_id":"2506.18881","n_code_links":0,"syntology":null},{"paper":null,"title":"TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge","date":"2025-06-23","arxiv_id":"2506.21618","n_code_links":0,"syntology":null},{"paper":null,"title":"Non-Euclidean Enriched Contraction Theory for Monotone Operators and Monotone Dynamical Systems","date":"2025-06-22","arxiv_id":"2506.17990","n_code_links":0,"syntology":null},{"paper":"/paper/taming-the-untamed-graph-based-knowledge","title":"Taming the Untamed: Graph-Based Knowledge Retrieval and Reasoning for MLLMs to Conquer the Unknown","date":"2025-06-21","arxiv_id":"2506.17589","n_code_links":0,"syntology":{"ran":4,"of":4,"unverified":0,"pointer_only":4}},{"paper":null,"title":"BIDA: A Bi-level Interaction Decision-making Algorithm for Autonomous Vehicles in Dynamic Traffic Scenarios","date":"2025-06-19","arxiv_id":"2506.16546","n_code_links":0,"syntology":null}],"papers_shown":30,"tasks":[{"task":"/task/language-modeling","name":"Language Modeling","papers":31},{"task":"/task/language-modelling","name":"Language Modelling","papers":31},{"task":"/task/semantic-segmentation","name":"Semantic Segmentation","papers":29},{"task":"/task/large-language-model","name":"Large Language Model","papers":26},{"task":"/task/retrieval","name":"Retrieval","papers":26},{"task":"/task/decision-making","name":"Decision Making","papers":24},{"task":"/task/denoising","name":"Denoising","papers":23},{"task":"/task/federated-learning","name":"Federated Learning","papers":23},{"task":"/task/image-generation","name":"Image Generation","papers":22},{"task":"/task/representation-learning","name":"Representation Learning","papers":21},{"task":"/task/decoder","name":"Decoder","papers":20},{"task":"/task/reinforcement-learning-1","name":"Reinforcement Learning (RL)","papers":20},{"task":"/task/contrastive-learning","name":"Contrastive Learning","papers":19},{"task":"/task/segmentation","name":"Segmentation","papers":18},{"task":"/task/diversity","name":"Diversity","papers":17},{"task":"/task/object","name":"Object","papers":17},{"task":"/task/question-answering","name":"Question Answering","papers":17},{"task":"/task/computational-efficiency","name":"Computational Efficiency","papers":15},{"task":"/task/fairness","name":"Fairness","papers":15},{"task":"/task/image-segmentation","name":"Image Segmentation","papers":15}],"tasks_shown":20,"n_tasks":546,"usage_by_year":[{"year":"2024","papers":204},{"year":"2025","papers":627}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/adopt"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}