| Phi-3 technical report: A highly capable language model locally on your phone M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... arXiv preprint arXiv:2404.14219, 2024 | 952 | 2024 |
| Textbooks are all you need S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ... arXiv preprint arXiv:2306.11644, 2023 | 585 | 2023 |
| Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions S Chen, S Chewi, J Li, Y Li, A Salim, AR Zhang The Eleventh International Conference on Learning Representations, 2022 | 317 | 2022 |
| Phi-2: The surprising power of small language models M Javaheripi, S Bubeck, M Abdin, J Aneja, S Bubeck, CCT Mendes, ... Microsoft Research Blog 1 (3), 3, 2023 | 228 | 2023 |
| Maximum mean discrepancy gradient flow M Arbel, A Korba, A Salim, A Gretton Advances in Neural Information Processing Systems 32, 2019 | 170 | 2019 |
| The probability flow ODE is provably fast S Chen, S Chewi, H Lee, Y Li, J Lu, A Salim Advances in Neural Information Processing Systems 36, 2023 | 105 | 2023 |
| A non-asymptotic analysis for Stein variational gradient descent A Korba, A Salim, M Arbel, G Luise, A Gretton Advances in Neural Information Processing Systems 33, 4672-4682, 2020 | 95 | 2020 |
| Optimal and practical algorithms for smooth and strongly convex decentralized optimization D Kovalev, A Salim, P Richtárik Advances in Neural Information Processing Systems 33, 18342-18352, 2020 | 94 | 2020 |
| Towards a theory of non-log-concave sampling: first-order stationarity guarantees for Langevin Monte Carlo K Balasubramanian, S Chewi, MA Erdogdu, A Salim, S Zhang Conference on Learning Theory, 2896-2923, 2022 | 76 | 2022 |
| Improved analysis for a proximal algorithm for sampling Y Chen, S Chewi, A Salim, A Wibisono Conference on Learning Theory, 2984-3014, 2022 | 70 | 2022 |
| The Wasserstein proximal gradient algorithm A Salim, A Korba, G Luise Advances in Neural Information Processing Systems 33, 12356-12366, 2020 | 64 | 2020 |
| Phi-4 technical report M Abdin, J Aneja, H Behl, S Bubeck, R Eldan, S Gunasekar, M Harrison, ... arXiv preprint arXiv:2412.08905, 2024 | 54 | 2024 |
| Dualize, split, randomize: Toward fast nonsmooth optimization algorithms A Salim, L Condat, K Mishchenko, P Richtárik Journal of Optimization Theory and Applications 195 (1), 102-130, 2022 | 44 | 2022 |
| Primal dual interpretation of the proximal stochastic gradient Langevin algorithm A Salim, P Richtarik Advances in Neural Information Processing Systems 33, 3786-3796, 2020 | 43 | 2020 |
| Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein space MZ Diao, K Balasubramanian, S Chewi, A Salim International Conference on Machine Learning, 7960-7991, 2023 | 37 | 2023 |
| Phi-3 technical report: A highly capable language model locally on your phone, 2024 M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... URL https://arxiv. org/abs/2404.14219, 2024 | 36 | 2024 |
| An optimal algorithm for strongly convex minimization under affine constraints A Salim, L Condat, D Kovalev, P Richtárik International conference on artificial intelligence and statistics, 4482-4498, 2022 | 31 | 2022 |
| Stochastic proximal Langevin algorithm: Potential splitting and nonasymptotic rates A Salim, D Kovalev, P Richtárik Advances in Neural Information Processing Systems 32, 2019 | 31 | 2019 |
| A convergence theory for SVGD in the population limit under Talagrand’s inequality T1 A Salim, L Sun, P Richtarik International Conference on Machine Learning, 19139-19152, 2022 | 30* | 2022 |
| A constant step Forward-Backward algorithm involving random maximal monotone operators P Bianchi, W Hachem, A Salim Journal of Convex Analysis 26 (2), 387-436, 2019 | 30 | 2019 |
Peter RichtarikProfessor, KAUST確認したメール アドレス: kaust.edu.sa