{"list":"other","total":58,"rows":[{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"2101.03961","title":"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity","created":"2021-01-11","cited_by_count":3073},{"id":"2106.01946","title":"Convex optimization","created":"2021-06-03","cited_by_count":2515},{"id":"2107.13586","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","created":"2021-07-28","cited_by_count":2234},{"id":"2002.05202","title":"GLU Variants Improve Transformer","created":"2020-02-12","cited_by_count":1804},{"id":"1910.07467","title":"Root Mean Square Layer Normalization","created":"2019-10-16","cited_by_count":1480},{"id":"2406.17557","title":"The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale","created":"2024-06-25","cited_by_count":1160},{"id":"1309.5549","title":"Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming","created":"2013-09-22","cited_by_count":724},{"id":"1802.04434","title":"signSGD: Compressed Optimisation for Non-Convex Problems","created":"2018-02-13","cited_by_count":571},{"id":"1905.11881","title":"Why gradient clipping accelerates training: A theoretical justification for adaptivity","created":"2019-05-28","cited_by_count":341},{"id":"1901.09847","title":"Error Feedback Fixes SignSGD and other Gradient Compression Schemes","created":"2019-01-28","cited_by_count":310},{"id":"1912.02365","title":"Lower Bounds for Non-Convex Stochastic Optimization","created":"2019-12-05","cited_by_count":307},{"id":"2003.00307","title":"Loss landscapes and optimization in over-parameterized non-linear systems and neural networks","created":"2020-02-29","cited_by_count":233},{"id":"1905.03871","title":"Differentially Private Learning with Adaptive Clipping","created":"2019-05-09","cited_by_count":220},{"id":"1901.06053","title":"A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks","created":"2019-01-18","cited_by_count":214},{"id":"2307.05695","title":"ReLoRA: High-Rank Training Through Low-Rank Updates","created":"2023-07-11","cited_by_count":204},{"id":"2010.05893","title":"Large-Scale Methods for Distributionally Robust Optimization","created":"2020-10-12","cited_by_count":179},{"id":"2006.15429","title":"Understanding Gradient Clipping in Private SGD: A Geometric Perspective","created":"2020-06-27","cited_by_count":142},{"id":"2002.03305","title":"Momentum Improves Normalized SGD","created":"2020-02-09","cited_by_count":139},{"id":"2012.10333","title":"Learning from History for Byzantine Robust Optimization","created":"2020-12-18","cited_by_count":137},{"id":"2006.04740","title":"The Heavy-Tail Phenomenon in SGD","created":"2020-06-08","cited_by_count":124},{"id":"2005.10785","title":"Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping","created":"2020-05-21","cited_by_count":104},{"id":"2304.13972","title":"Convergence of Adam Under Relaxed Assumptions","created":"2023-04-27","cited_by_count":99},{"id":"2010.02519","title":"Improved Analysis of Clipping Algorithms for Non-convex Optimization","created":"2020-10-05","cited_by_count":89},{"id":"2305.01588","title":"Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees","created":"2023-05-02","cited_by_count":83},{"id":"2208.11195","title":"Robustness to Unbounded Smoothness of Generalized SignSGD","created":"2022-08-23","cited_by_count":81},{"id":"2106.14343","title":"High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails","created":"2021-06-28","cited_by_count":80},{"id":"1507.02030","title":"Beyond Convexity: Stochastic Quasi-Convex Optimization","created":"2015-07-08","cited_by_count":76},{"id":"2007.14294","title":"A High Probability Analysis of Adaptive SGD with Momentum","created":"2020-07-28","cited_by_count":61},{"id":"2302.00999","title":"High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance","created":"2023-02-02","cited_by_count":61},{"id":"2305.18471","title":"Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions","created":"2023-05-29","cited_by_count":57},{"id":"1905.12938","title":"Stochastic Sign Descent Methods: New Algorithms and Better Theory","created":"2019-05-30","cited_by_count":49},{"id":"2410.13849","title":"From Gradient Clipping to Normalization for Heavy Tailed SGD","created":"2024-10-17","cited_by_count":49},{"id":"2306.01264","title":"Convex and Non-convex Optimization Under Generalized Smoothness","created":"2023-06-02","cited_by_count":44},{"id":"2407.07972","title":"Deconstructing What Makes a Good Optimizer for Language Models","created":"2024-07-10","cited_by_count":41},{"id":"2110.12459","title":"Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis","created":"2021-10-24","cited_by_count":39},{"id":"2303.02854","title":"Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization","created":"2023-03-06","cited_by_count":35},{"id":"1907.02707","title":"Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method","created":"2019-07-05","cited_by_count":32},{"id":"2208.09900","title":"Provable Adaptivity of Adam under Non-uniform Smoothness","created":"2022-08-21","cited_by_count":30},{"id":"2311.03252","title":"Parameter-Agnostic Optimization under Relaxed Smoothness","created":"2023-11-06","cited_by_count":29},{"id":"2302.06763","title":"Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise","created":"2023-02-14","cited_by_count":27},{"id":"2409.14989","title":"Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity","created":"2024-09-23","cited_by_count":25},{"id":"2305.12475","title":"Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods","created":"2023-05-21","cited_by_count":23},{"id":"2411.15958","title":"Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise","created":"2024-11-24","cited_by_count":23},{"id":"2303.00883","title":"Variance-reduced Clipping for Non-convex Optimization","created":"2023-03-02","cited_by_count":22},{"id":"2311.04161","title":"Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems","created":"2023-11-07","cited_by_count":21},{"id":"2205.05040","title":"A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks","created":"2022-05-10","cited_by_count":20},{"id":"2204.02593","title":"Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise","created":"2022-04-06","cited_by_count":16},{"id":"2401.09587","title":"Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis","created":"2024-01-17","cited_by_count":15},{"id":"2403.15146","title":"On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond","created":"2024-03-22","cited_by_count":14},{"id":"2404.01436","title":"Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance","created":"2024-04-01","cited_by_count":14},{"id":"2011.12433","title":"Optimal Mean Estimation without a Variance","created":"2020-11-24","cited_by_count":13},{"id":"2304.01119","title":"Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tails","created":"2023-04-03","cited_by_count":13},{"id":"2310.18763","title":"Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance","created":"2023-10-28","cited_by_count":10},{"id":"2310.18784","title":"High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise","created":"2023-10-28","cited_by_count":7},{"id":"2405.19440","title":"MGDA Converges under Generalized Smoothness, Provably","created":"2024-05-29","cited_by_count":7},{"id":"2412.20017","title":"A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness","created":"2024-12-28","cited_by_count":7}],"next_cursor":null}