Do imagenet classifiers generalize to imagenet? B Recht, R Roelofs, L Schmidt, V Shankar International Conference on Machine Learning, 5389-5400, 2019 | 721* | 2019 |
Cloud programming simplified: A berkeley view on serverless computing E Jonas, J Schleier-Smith, V Sreekanti, CC Tsai, A Khandelwal, Q Pu, ... arXiv preprint arXiv:1902.03383, 2019 | 388 | 2019 |
Measuring robustness to natural distribution shifts in image classification R Taori, A Dave, V Shankar, N Carlini, B Recht, L Schmidt Advances in Neural Information Processing Systems 33, 18583-18599, 2020 | 164 | 2020 |
Better malware ground truth: Techniques for weighting anti-virus vendor labels A Kantchelian, MC Tschantz, S Afroz, B Miller, V Shankar, R Bachwani, ... Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security …, 2015 | 108 | 2015 |
A meta-analysis of overfitting in machine learning R Roelofs, V Shankar, B Recht, S Fridovich-Keil, M Hardt, J Miller, ... Advances in Neural Information Processing Systems 32, 2019 | 80 | 2019 |
Numpywren: Serverless linear algebra V Shankar, K Krauth, Q Pu, E Jonas, S Venkataraman, I Stoica, B Recht, ... arXiv preprint arXiv:1810.09679, 2018 | 75* | 2018 |
Reviewer integration and performance measurement for malware detection B Miller, A Kantchelian, MC Tschantz, S Afroz, R Bachwani, ... International Conference on Detection of Intrusions and Malware, and …, 2016 | 61 | 2016 |
Flare prediction using photospheric and coronal image data E Jonas, M Bobra, V Shankar, J Todd Hoeksema, B Recht Solar Physics 293 (3), 1-22, 2018 | 60 | 2018 |
Evaluating machine accuracy on imagenet V Shankar, R Roelofs, H Mania, A Fang, B Recht, L Schmidt International Conference on Machine Learning, 8634-8644, 2020 | 57 | 2020 |
Neural kernels without tangents V Shankar, A Fang, W Guo, S Fridovich-Keil, J Ragan-Kelley, L Schmidt, ... International Conference on Machine Learning, 8614-8623, 2020 | 53 | 2020 |
Do image classifiers generalize across time? V Shankar, A Dave, R Roelofs, D Ramanan, B Recht, L Schmidt Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 51* | 2021 |
Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization JP Miller, R Taori, A Raghunathan, S Sagawa, PW Koh, V Shankar, ... International Conference on Machine Learning, 7721-7735, 2021 | 30 | 2021 |
Convolutional kitchen sinks for transcription factor binding site prediction A Morrow, V Shankar, D Petersohn, A Joseph, B Recht, N Yosef arXiv preprint arXiv:1706.00125, 2017 | 15 | 2017 |
A generalizable and accessible approach to machine learning with global satellite imagery E Rolf, J Proctor, T Carleton, I Bolliger, V Shankar, M Ishihara, B Recht, ... Nature communications 12 (1), 1-11, 2021 | 14 | 2021 |
Predicting with confidence on unseen distributions D Guillory, V Shankar, S Ebrahimi, T Darrell, L Schmidt Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 11 | 2021 |
Serverless straggler mitigation using error-correcting codes V Gupta, D Carrano, Y Yang, V Shankar, T Courtade, K Ramchandran 2020 IEEE 40th International Conference on Distributed Computing Systems …, 2020 | 9* | 2020 |
Back to the future: Malware detection with temporally consistent labels B Miller, A Kantchelian, S Afroz, R Bachwani, R Faizullabhoy, L Huang, ... Under submission, 2015 | 6 | 2015 |
Approximate subgraph isomorphism for image localization V Shankar, J Zhang, J Chen, C Dinh, M Clements, A Zakhor Electronic Imaging 2016 (15), 1-9, 2016 | 1 | 2016 |
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP) A Fang, G Ilharco, M Wortsman, Y Wan, V Shankar, A Dave, L Schmidt arXiv preprint arXiv:2205.01397, 2022 | | 2022 |
From Distribution Shift to Kernel Methods: A study of empirical phenomena in machine learning V Shankar University of California, Berkeley, 2020 | | 2020 |