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Rishabh Iyer
Rishabh Iyer
Bestätigte E-Mail-Adresse bei utdallas.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Submodularity in data subset selection and active learning
K Wei, R Iyer, J Bilmes
International conference on machine learning, 1954-1963, 2015
4522015
Submodular optimization with submodular cover and submodular knapsack constraints
RK Iyer, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2436-2444, 2013
3032013
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
2352014
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
187*2021
Algorithms for approximate minimization of the difference between submodular functions, with applications
R Iyer, J Bilmes
Uncertainty in Artificial Intelligence (UAI), 2012
1842012
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
1702021
Fast semidifferential-based submodular function optimization
R Iyer, S Jegelka, J Bilmes
International Conference on Machine Learning (ICML), 2013
1432013
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
1062014
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
952022
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
862021
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
862019
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
732021
Submodular combinatorial information measures with applications in machine learning
R Iyer, N Khargoankar, J Bilmes, H Asanani
Algorithmic Learning Theory, 722-754, 2021
732021
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
61*2022
Submodular-Bregman and the Lovasz-Bregman Divergences with Applications
R Iyer, J Bilmes
Advances in Neural Information Processing Systems (NIPS), 2942-2950, 2012
552012
Active machine learning
DM Chickering, CA Meek, PY Simard, RK Iyer
US Patent 10,262,272, 2019
492019
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
472015
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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