Browsing by Author Gu, Quanquan

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TitleAuthor(s)Issue Date
 
Benign Overfitting in Two-layer Convolutional Neural Networks
Proceeding/Conference:NeurIPS 2022 (28/11/2022-09/12/2022, New Orleans )
Cao, YuanChen, ZixiangBelkin, MikhailGu, Quanquan
9-Dec-2022
 
Closing the generalization gap of adaptive gradient methods in training deep neural networks
Proceeding/Conference:Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Chen, JinghuiZhou, DongruoTang, YiqiYang, ZiyanCao, YuanGu, Quanquan
2020
 
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
Journal:Proceedings of the National Academy of Sciences of the United States of America
Cramer, Estee Y.Ray, Evan L.Lopez, Velma K.Bracher, JohannesBrennen, AndreaCastro Rivadeneira, Alvaro J.Gerding, AaronGneiting, TilmannHouse, Katie H.Huang, YuxinJayawardena, DasuniTurtle, James A.Ben-Nun, MichalRiley, StevenRiley, PeteKoyluoglu, UgurDesRoches, DavidForli, PedroHamory, BruceKyriakides, ChristinaLeis, HelenKanji, Abdul H.Milliken, JohnMoloney, MichaelMorgan, JamesNirgudkar, NinadOzcan, GokcePiwonka, NoahRavi, MattSchrader, ChrisShakhnovich, ElizabethSiegel, DanielKhandelwal, AyushSpatz, RyanStiefeling, ChrisWilkinson, BarrieWong, AlexanderCavany, SeanEspaña, GuidoMoore, SeanOidtman, RachelPerkins, AlexKraus, DavidLe, KhoaKraus, AndreaGao, ZhifengBian, JiangCao, WeiLavista Ferres, JuanLi, ChaozhuoLiu, Tie YanXie, XingZhang, ShunZheng, ShunMühlemann, AnjaVespignani, AlessandroChinazzi, MatteoDavis, Jessica T.Mu, KunpengPastore Y Piontti, AnaXiong, XinyueZheng, AndrewBaek, JackieFarias, VivekGeorgescu, AndreeaNiemi, JaradLevi, RetsefSinha, DeekshaWilde, JoshuaPerakis, GeorgiaBennouna, Mohammed AmineNze-Ndong, DavidSinghvi, DivyaSpantidakis, IoannisThayaparan, LeannTsiourvas, AsteriosShah, ApurvSarker, ArnabJadbabaie, AliShah, DevavratDella Penna, NicolasCeli, Leo A.Sundar, SakethWolfinger, RussOsthus, DaveCastro, LaurenFairchild, GeoffreyStark, ArianeMichaud, IsaacKarlen, DeanKinsey, MattMullany, Luke C.Rainwater-Lovett, KaitlinShin, LaurenTallaksen, KatharineWilson, ShelbyLee, Elizabeth C.Dent, JuanWang, YijinGrantz, Kyra H.Hill, Alison L.Kaminsky, JoshuaKaminsky, KathrynKeegan, Lindsay T.Lauer, Stephen A.Lemaitre, Joseph C.Lessler, JustinMeredith, Hannah R.Perez-Saez, JavierWattanachit, NutchaShah, SamSmith, Claire P.Truelove, Shaun A.Wills, JoshMarshall, MaximilianGardner, LaurenNixon, KristenBurant, John C.Wang, LilyGao, LeiZorn, Martha W.Gu, ZhilingKim, MyungjinLi, XinyiWang, GuannanWang, YueyingYu, ShanReiner, Robert C.Barber, RyanGakidou, EmmanuelaHay, Simon I.Gu, YouyangLim, SteveMurray, ChrisPigott, DavidGurung, Heidi L.Baccam, PrasithStage, Steven A.Suchoski, Bradley T.Prakash, B. AdityaAdhikari, BijayaCui, JiamingJain, SansiddhRodríguez, AlexanderTabassum, AnikaXie, JiajiaKeskinocak, PinarAsplund, JohnBaxter, ArdenOruc, Buse EylulSerban, NicoletaArik, Sercan O.Dusenberry, MikeBannur, NayanaEpshteyn, ArkadyKanal, ElliLe, Long T.Li, Chun LiangPfister, TomasSava, DarioSinha, RajarishiTsai, ThomasYoder, NateYoon, JinsungDeva, AyushZhang, LeyouAbbott, SamBosse, Nikos I.Funk, SebastianHellewell, JoelMeakin, Sophie R.Sherratt, KatharineZhou, MingyuanKalantari, RahiYamana, Teresa K.Kulkarni, MihirPei, SenShaman, JeffreyLi, Michael L.Bertsimas, DimitrisSkali Lami, OmarSoni, SakshamTazi Bouardi, HamzaAyer, TurgayAdee, MadelineChhatwal, JagpreetMerugu, SrujanaDalgic, Ozden O.Ladd, Mary A.Linas, Benjamin P.Mueller, PeterXiao, JadeWang, YuanjiaWang, QinxiaXie, ShanghongZeng, DonglinGreen, AldenRaval, AlpanBien, JacobBrooks, LoganHu, Addison J.Jahja, MariaMcDonald, DanielNarasimhan, BalasubramanianPolitsch, CollinRajanala, SamyakRumack, AaronSimon, NoahShingi, SiddhantTibshirani, Ryan J.Tibshirani, RobVentura, ValerieWasserman, LarryO'Dea, Eamon B.Drake, John M.Pagano, RobertTran, Quoc T.Ho, Lam Si TungHuynh, HuongTiwari, AvtanshWalker, Jo W.Slayton, Rachel B.Johansson, Michael A.Biggerstaff, MatthewReich, Nicholas G.White, JeromeAbernethy, Neil F.Woody, SpencerDahan, MaytalFox, SpencerGaither, KellyLachmann, MichaelMeyers, Lauren AncelScott, James G.Tec, MauricioSrivastava, AjiteshGeorge, Glover E.Cegan, Jeffrey C.Dettwiller, Ian D.England, William P.Farthing, Matthew W.Hunter, Robert H.Lafferty, BrandonLinkov, IgorMayo, Michael L.Parno, Matthew D.Rowland, Michael A.Trump, Benjamin D.Zhang-James, YanliChen, SamuelFaraone, Stephen V.Hess, JonathanMorley, Christopher P.Salekin, AsifWang, DongliangCorsetti, Sabrina M.Baer, Thomas M.Eisenberg, Marisa C.Falb, KarlHuang, YitaoMartin, Emily T.McCauley, EllaMyers, Robert L.Schwarz, TomSheldon, DanielGibson, Graham CaseyYu, RoseGao, LiyaoMa, YianWu, DongxiaYan, XifengJin, XiaoyongWang, Yu XiangChen, Yang QuanGuo, LihongZhao, YantingGu, QuanquanChen, JinghuiWang, LingxiaoXu, PanZhang, WeitongZou, DifanBiegel, HannahLega, JocelineMcConnell, SteveNagraj, V. P.Guertin, Stephanie L.Hulme-Lowe, ChristopherTurner, Stephen D.Shi, YunfengBan, XuegangWalraven, RobertHong, Qi JunKong, Stanleyvan de Walle, Axel
2022
 
Generalization bounds of stochastic gradient descent for wide and deep neural networks
Proceeding/Conference:Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
Cao, YuanGu, Quanquan
2019
 
Generalization error bounds of gradient descent for learning over-parameterized deep relu networks
Proceeding/Conference:Proceedings of the AAAI Conference on Artificial Intelligence
Cao, YuanGu, Quanquan
2020
 
Gradient descent optimizes over-parameterized deep ReLU networks
Journal:Machine Learning
Zou, DifanCao, YuanZhou, DongruoGu, Quanquan
2020
 
Layer-dependent importance sampling for training deep and large graph convolutional networks
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanHu, ZiniuWang, YewenJiang, SongSun, YizhouGu, Quanquan
2019
 
Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples
Proceeding/Conference:International Conference on Machine Learning (17/07/2022-23/07/2022, Baltimore)
Wu, JingfengZou, DifanChen, ZixiangBraverman, VladimirGu, QuanquanKakade, Sham M
23-Jul-2022
 
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Journal:Transactions on Machine Learning Research
Zhou, DongruoChen, JinghuiCao, YuanYang, ZiyanGu, Quanquan
16-Mar-2024
 
Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Proceeding/Conference:Advances in Neural Information Processing Systems (28/11/2022-09/12/2022, New Orleans)
Zou, DifanWu, JingfengBraverman, VladimirGu, QuanquanKakade, Sham M
12-Dec-2022
 
Sampling from non-log-concave distributions via stochastic variance-reduced gradient Langevin dynamics
Proceeding/Conference:AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics
Zou, DifanXu, PanGu, Quanquan
2020
 
Stochastic gradient hamiltonian monte carlo methods with recursive variance reduction
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanXu, PanGu, Quanquan
2019
 
Stochastic variance-reduced Hamilton Monte Carlo methods
Proceeding/Conference:35th International Conference on Machine Learning, ICML 2018
Zou, DifanXu, PanGu, Quanquan
2018
 
The Benefits of Implicit Regularization from SGD in Least Squares Problems
Proceeding/Conference:Advances in Neural Information Processing Systems
Zou, DifanWu, JingfengBraverman, VladimirGu, QuanquanFoster, Dean P.Kakade, Sham M.
2021
 
The Benefits of Mixup for Feature Learning
Proceeding/Conference:Fortieth International Conference on Machine Learning (ICML) (23/07/2023-29/07/2023, Honolulu, Hawaii, USA)
Zou, DifanCao, YuanLi, YuanzhiGu, Quanquan
23-Jul-2023
 
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift
Proceeding/Conference:Advances in Neural Information Processing Systems (28/11/2022-09/12/2022, New Orleans)
Wu, JingfengZou, DifanBraverman, VladimirGu, QuanquanKakade, and Sham M
12-Dec-2022
 
Tight sample complexity of learning one-hidden-layer convolutional neural networks
Proceeding/Conference:Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
Cao, YuanGu, Quanquan
2019
 
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Proceeding/Conference:International Conference on Learning Representations (ICLR 2023) (01/05/2023-05/05/2023, Kigali, Rwanda)
Zou, DifanCao, YuanLi, YuanzhiGu, Quanquan
5-May-2023
 
Understanding Train-Validation Split in Meta-Learning with Neural Networks
Proceeding/Conference:The 11th International Conference on Learning Representations (ICLR 2023) (01/05/2023-05/05/2023, Kigali, Rwanda)
Zuo, XinzheChen, ZixiangYao, HuaxiuCao, YuanGu, Quanquan
5-May-2023
Showing results 5 to 23 of 23 < previous