Ashok Chandrashekar

Publication Activity (10 Years)

Years Active: 1998-2023
Publications (10 Years): 12

Top Topics

Unlabeled Images

Collaborative Filtering

Top Venues

Publications

Claudia V. Roberts, Ehtsham Elahi, Ashok Chandrashekar
CLIME: Completeness-Constrained LIME. WWW (Companion Volume) (2023)
Claudia V. Roberts, Ehtsham Elahi, Ashok Chandrashekar
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks. CoRR (2022)
Claudia V. Roberts, Maria Dimakopoulou, Qifeng Qiao, Ashok Chandrashekar, Tony Jebara
Selectively Contextual Bandits. CoRR (2022)
Mahdi M. Kalayeh, Shervin Ardeshir, Lingyi Liu, Nagendra Kamath, Ashok Chandrashekar
On Negative Sampling for Audio-Visual Contrastive Learning from Movies. CoRR (2022)
Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus
Control Variates for Slate Off-Policy Evaluation. CoRR (2021)
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 (2021)
Pannaga Shivaswamy, Ashok Chandrashekar
Bias-Variance Decomposition for Ranking. WSDM (2021)
Nikos Vlassis, Fernando Amat Gil, Ashok Chandrashekar
Off-Policy Evaluation of Slate Policies under Bayes Risk. CoRR (2021)
Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus
Control Variates for Slate Off-Policy Evaluation. NeurIPS (2021)
Ehtsham Elahi, Ashok Chandrashekar
Learning Representations of Hierarchical Slates in Collaborative Filtering. RecSys (2020)
Ehtsham Elahi, Ashok Chandrashekar
Learning Representations of Hierarchical Slates in Collaborative Filtering. CoRR (2020)
Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico
Artwork personalization at netflix. RecSys (2018)
Ashok Chandrashekar, Lorenzo Torresani, Richard Granger
Learning what is where from unlabeled images: joint localization and clustering of foreground objects. Mach. Learn. 94 (2) (2014)
Ashok Chandrashekar, Richard Granger
Derivation of a Novel Efficient Supervised Learning Algorithm from Cortical-Subcortical Loops. Frontiers Comput. Neurosci. 5 (2011)
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)
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) (1998)