Mikhail Khodak

Dikutip oleh

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Ameet TalwalkarCMU, DatadogEmail yang diverifikasi di cmu.edu
Nikunj SaunshiResearch Scientist, GoogleEmail yang diverifikasi di google.com
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityEmail yang diverifikasi di cs.cmu.edu
Sanjeev AroraProfessor of Computer Science, Princeton UniversityEmail yang diverifikasi di princeton.edu
Liam LiCarnegie Mellon UniversityEmail yang diverifikasi di liamcli.com
Kiran VodrahalliResearch Scientist, Google DeepMindEmail yang diverifikasi di google.com
Hrishikesh KhandeparkarQuantitative Researcher, Citadel SecuritiesEmail yang diverifikasi di alumni.princeton.edu
Junhong ShenPh.D. student in Machine Learning, Carnegie Mellon UniversityEmail yang diverifikasi di andrew.cmu.edu
Nicholas RobertsPhD student UW-MadisonEmail yang diverifikasi di cs.wisc.edu
Renbo TuUniversity of TorontoEmail yang diverifikasi di mail.utoronto.ca
Virginia SmithCarnegie Mellon UniversityEmail yang diverifikasi di cmu.edu
Tian LiUniversity of ChicagoEmail yang diverifikasi di uchicago.edu
Sergei VassilvitskiiGoogleEmail yang diverifikasi di google.com
Jeffrey LiUniversity of WashingtonEmail yang diverifikasi di cs.washington.edu
Nicolò FusiPartner Researcher, Microsoft ResearchEmail yang diverifikasi di microsoft.com
Neil TenenholtzMicrosoft ResearchEmail yang diverifikasi di microsoft.com
Lester MackeyMicrosoft ResearchEmail yang diverifikasi di microsoft.com
Tri DaoPrinceton University, Together AIEmail yang diverifikasi di princeton.edu
Christopher RéComputer Science, Stanford UniversityEmail yang diverifikasi di cs.stanford.edu
Yingyu LiangUW-MadisonEmail yang diverifikasi di cs.wisc.edu

Ikuti

Mikhail Khodak

CMU

Email yang diverifikasi di cs.princeton.edu


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and trends® in machine learning 14 (1–2), 1-210, 2021	7436	2021
A theoretical analysis of contrastive unsupervised representation learning S Arora, H Khandeparkar, M Khodak, O Plevrakis, N Saunshi ICML, 2019	912*	2019
Adaptive gradient-based meta-learning methods M Khodak, MF Balcan, A Talwalkar NeurIPS, 2019	425	2019
A large self-annotated corpus for sarcasm M Khodak, N Saunshi, K Vodrahalli LREC, 2017	300	2017
Provable guarantees for gradient-based meta-learning M Khodak, MF Balcan, A Talwalkar ICML, 2019	183*	2019
Differentially private meta-learning J Li, M Khodak, S Caldas, A Talwalkar ICLR, 2019	162	2019
A la carte embedding: Cheap but effective induction of semantic feature vectors M Khodak, N Saunshi, Y Liang, T Ma, B Stewart, S Arora ACL, 2018	136	2018
Federated hyperparameter tuning: Challenges, baselines, and connections to weight-sharing M Khodak, R Tu, T Li, L Li, MFF Balcan, V Smith, A Talwalkar Advances in Neural Information Processing Systems 34, 19184-19197, 2021	107*	2021
Geometry-Aware Gradient Algorithms for Neural Architecture Search L Li, M Khodak, MF Balcan, A Talwalkar ICLR, 2020	86	2020
Initialization and Regularization of Factorized Neural Layers M Khodak, N Tenenholtz, L Mackey, N Fusi ICLR, 2021	64	2021
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks R Tu, N Roberts, M Khodak, J Shen, F Sala, A Talwalkar	60*	2022
Cross-modal fine-tuning: Align then refine J Shen, L Li, LM Dery, C Staten, M Khodak, G Neubig, A Talwalkar International Conference on Machine Learning, 31030-31056, 2023	57	2023
A compressed sensing view of unsupervised text embeddings, bag-of-n-grams, and LSTMs S Arora, M Khodak, N Saunshi, K Vodrahalli ICLR, 2018	54	2018
Automated wordnet construction using word embeddings M Khodak, A Risteski, C Fellbaum, S Arora SENSE, 12-23, 2017	50	2017
Efficient architecture search for diverse tasks J Shen, M Khodak, A Talwalkar Advances in Neural Information Processing Systems 35, 16151-16164, 2022	44	2022
A deeper look at zero-cost proxies for lightweight NAS C White, M Khodak, R Tu, S Shah, S Bubeck ICLR Blog Track 445, 2022	39	2022
Rethinking neural operations for diverse tasks N Roberts, M Khodak, T Dao, L Li, C Ré, A Talwalkar Advances in Neural Information Processing Systems 34, 15855-15869, 2021	35	2021
Learning predictions for algorithms with predictions M Khodak, MFF Balcan, A Talwalkar, S Vassilvitskii Advances in Neural Information Processing Systems 35, 3542-3555, 2022	31	2022
Learning cloud dynamics to optimize spot instance bidding strategies M Khodak, L Zheng, AS Lan, C Joe-Wong, M Chiang INFOCOM, 2762-2770, 2018	31	2018
Direct fusion drive for interstellar exploration SA Cohen, C Swanson, N McGreivy, A Raja, E Evans, P Jandovitz, ... JBIS-Journal of the British Interplanetary Society 72 (2), 37-50, 2019	30	2019

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