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Ashok Chandrashekar
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2020 – today
- 2024
- [c7]Bora Edizel
, Tim Sweetser
Towards Understanding The Gaps of Offline And Online Evaluation Metrics: Impact of Series vs. Movie Recommendations. RecSys 2024: 844-846 - 2023
- [c6]Claudia V. Roberts
CLIME: Completeness-Constrained LIME. WWW (Companion Volume) 2023: 950-958 - 2022
- [i7]Mahdi M. Kalayeh, Shervin Ardeshir, Lingyi Liu, Nagendra Kamath, Ashok Chandrashekar:
On Negative Sampling for Audio-Visual Contrastive Learning from Movies. CoRR abs/2205.00073 (2022) - [i6]Claudia V. Roberts, Maria Dimakopoulou, Qifeng Qiao, Ashok Chandrashekar, Tony Jebara:
Selectively Contextual Bandits. CoRR abs/2205.04528 (2022) - [i5]Claudia V. Roberts, Ehtsham Elahi, Ashok Chandrashekar:
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks. CoRR abs/2206.04784 (2022) - 2021
- [c5]Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus:
Control Variates for Slate Off-Policy Evaluation. NeurIPS 2021: 3667-3679 - [c4]Pannaga Shivaswamy, Ashok Chandrashekar:
Bias-Variance Decomposition for Ranking. WSDM 2021: 472-480 - [i4]Nikos Vlassis, Fernando Amat Gil, Ashok Chandrashekar:
Off-Policy Evaluation of Slate Policies under Bayes Risk. CoRR abs/2101.02553 (2021) - [i3]Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus:
Control Variates for Slate Off-Policy Evaluation. CoRR abs/2106.07914 (2021) - [i2]Mahdi M. Kalayeh, Nagendra Kamath, Lingyi Liu, Ashok Chandrashekar:
Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows. CoRR abs/2106.08513 (2021) - 2020
- [c3]Ehtsham Elahi, Ashok Chandrashekar:
Learning Representations of Hierarchical Slates in Collaborative Filtering. RecSys 2020: 703-707 - [i1]Ehtsham Elahi, Ashok Chandrashekar:
Learning Representations of Hierarchical Slates in Collaborative Filtering. CoRR abs/2010.06987 (2020)
2010 – 2019
- 2018
- [c2]Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico:
Artwork personalization at netflix. RecSys 2018: 487-488 - 2014
- [j3]Ashok Chandrashekar, Lorenzo Torresani, Richard Granger:
Learning what is where from unlabeled images: joint localization and clustering of foreground objects. Mach. Learn. 94(2): 261-279 (2014) - 2011
- [j2]Ashok Chandrashekar, Richard Granger:
Derivation of a Novel Efficient Supervised Learning Algorithm from Cortical-Subcortical Loops. Frontiers Comput. Neurosci. 5: 50 (2011)
2000 – 2009
- 2007
- [c1]Jeff Furlong, Andrew Felch, Jayram Moorkanikara Nageswaran, Nikil D. Dutt, Alex Nicolau, Alexander V. Veidenbaum, Ashok Chandrashekar, Richard Granger:
Novel Brain-Derived Algorithms Scale Linearly with Number of Processing Elements. PARCO 2007: 767-776
1990 – 1999
- 1998
- [j1]Ashok Chandrashekar, Thomas E. Callarman:
A modelling study of the effects of continuous incremental improvement in the case of a process shop. Eur. J. Oper. Res. 109(1): 111-121 (1998)
Coauthor Index
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