Следене
Rishabh Iyer
Rishabh Iyer
University of Texas Dallas, Microsoft, UW
Потвърден имейл адрес: utdallas.edu - Начална страница
Заглавие
Позовавания
Позовавания
Година
Submodularity in data subset selection and active learning
K Wei, R Iyer, J Bilmes
International conference on machine learning, 1954-1963, 2015
4402015
Submodular optimization with submodular cover and submodular knapsack constraints
RK Iyer, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2436-2444, 2013
2982013
Learning mixtures of submodular functions for image collection summarization
S Tschiatschek, RK Iyer, H Wei, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 1413-1421, 2014
2302014
Algorithms for approximate minimization of the difference between submodular functions, with applications
R Iyer, J Bilmes
Uncertainty in Artificial Intelligence (UAI), 2012
1812012
Glister: A generalization based data selection framework for efficient and robust learning
K Killamsetty, D Subramanian, G Ramakrishnan, R Iyer
Proceedings of the AAAI Conference on Artificial Intelligence, 2021
163*2021
Grad-match: Gradient matching based data subset selection for efficient deep model training
K Killamsetty, S Durga, G Ramakrishnan, A De, R Iyer
International Conference on Machine Learning, 5464-5474, 2021
1512021
Fast semidifferential-based submodular function optimization
R Iyer, S Jegelka, J Bilmes
International Conference on Machine Learning (ICML), 2013
1412013
Curvature and optimal algorithms for learning and minimizing submodular functions
RK Iyer, S Jegelka, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2742-2750, 2013
1182013
Fast multi-stage submodular maximization
K Wei, R Iyer, J Bilmes
International Conference on Machine Learning (ICML-14), 1494-1502, 2014
1052014
Learning from less data: A unified data subset selection and active learning framework for computer vision
V Kaushal, R Iyer, S Kothawade, R Mahadev, K Doctor, G Ramakrishnan
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 1289-1299, 2019
852019
Similar: Submodular information measures based active learning in realistic scenarios
S Kothawade, N Beck, K Killamsetty, R Iyer
Advances in Neural Information Processing Systems 34, 18685-18697, 2021
822021
Gcr: Gradient coreset based replay buffer selection for continual learning
R Tiwari, K Killamsetty, R Iyer, P Shenoy
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
792022
Submodular combinatorial information measures with applications in machine learning
R Iyer, N Khargoankar, J Bilmes, H Asanani
Algorithmic Learning Theory, 722-754, 2021
702021
Retrieve: Coreset selection for efficient and robust semi-supervised learning
K Killamsetty, X Zhao, F Chen, R Iyer
Advances in neural information processing systems 34, 14488-14501, 2021
592021
Prism: A rich class of parameterized submodular information measures for guided data subset selection
S Kothawade, V Kaushal, G Ramakrishnan, J Bilmes, R Iyer
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 10238 …, 2022
56*2022
Submodular-Bregman and the Lovasz-Bregman Divergences with Applications
R Iyer, J Bilmes
Advances in Neural Information Processing Systems (NIPS), 2942-2950, 2012
532012
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures
RB Bairi, R Iyer, G Ramakrishnan, J Bilmes
In Association of Computational Linguists (ACL) 2015, 2015
452015
Active machine learning
DM Chickering, CA Meek, PY Simard, RK Iyer
US Patent 10,262,272, 2019
442019
Algorithms for optimizing the ratio of submodular functions
W Bai, R Iyer, K Wei, J Bilmes
International Conference on Machine Learning, 2751-2759, 2016
442016
Mixed robust/average submodular partitioning: Fast algorithms, guarantees, and applications
K Wei, RK Iyer, S Wang, W Bai, JA Bilmes
Advances in Neural Information Processing Systems 28, 2015
442015
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