Prati
Rishabh Iyer
Naslov
Citirano
Citirano
Godina
Submodularity in data subset selection and active learning
K Wei, R Iyer, J Bilmes
International conference on machine learning, 1954-1963, 2015
3432015
Submodular optimization with submodular cover and submodular knapsack constraints
RK Iyer, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2436-2444, 2013
2592013
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
2082014
Algorithms for approximate minimization of the difference between submodular functions, with applications
R Iyer, J Bilmes
Uncertainty in Artificial Intelligence (UAI), 2012
1632012
Fast semidifferential-based submodular function optimization
R Iyer, S Jegelka, J Bilmes
International Conference on Machine Learning (ICML), 2013
1332013
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
1112013
Fast multi-stage submodular maximization
K Wei, R Iyer, J Bilmes
International Conference on Machine Learning (ICML-14), 1494-1502, 2014
942014
Glister: A generalization based data selection framework for efficient and robust learning
K Killamsetty, D Subramanian, G Ramakrishnan, R Iyer
AAAI, 2021
91*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
822021
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
65*2019
Submodular-Bregman and the Lovasz-Bregman Divergences with Applications
R Iyer, J Bilmes
Advances in Neural Information Processing Systems (NIPS), 2942-2950, 2012
512012
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
442021
Submodular combinatorial information measures with applications in machine learning
R Iyer, N Khargoankar, J Bilmes, H Asanani
Algorithmic Learning Theory, 722-754, 2021
442021
Algorithms for optimizing the ratio of submodular functions
W Bai, R Iyer, K Wei, J Bilmes
International Conference on Machine Learning, 2751-2759, 2016
412016
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
402015
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
392015
Active machine learning
DM Chickering, CA Meek, PY Simard, RK Iyer
US Patent 10,262,272, 2019
342019
Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications
R Iyer
Ph.D Dissertation, 2015
332015
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
32*2022
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
312021
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