A modelling study of the effects of continuous incremental improvement in the case of a process shop. - Ashok Chandrashekar; Thomas E. Callarman (Eur. J. Oper. Res., 1998)

Novel Brain-Derived Algorithms Scale Linearly with Number of Processing Elements. - Jeff Furlong; Andrew Felch; Jayram Moorkanikara Nageswaran; Nikil D. Dutt; Alex Nicolau; Alexander V. Veidenbaum; Ashok Chandrashekar; Richard Granger (PARCO, 2007)

Derivation of a Novel Efficient Supervised Learning Algorithm from Cortical-Subcortical Loops. - Ashok Chandrashekar; Richard Granger (Frontiers Comput. Neurosci., 2011)

Learning what is where from unlabeled images: joint localization and clustering of foreground objects. - Ashok Chandrashekar; Lorenzo Torresani; Richard Granger (Mach. Learn., 2014)

Artwork personalization at netflix. - Fernando Amat Gil; Ashok Chandrashekar; Tony Jebara; Justin Basilico (RecSys, 2018)

Learning Representations of Hierarchical Slates in Collaborative Filtering. - Ehtsham Elahi; Ashok Chandrashekar (RecSys, 2020)

Control Variates for Slate Off-Policy Evaluation. - Nikos Vlassis; Ashok Chandrashekar; Fernando Amat Gil; Nathan Kallus (NeurIPS, 2021)

Bias-Variance Decomposition for Ranking. - Pannaga Shivaswamy; Ashok Chandrashekar (WSDM, 2021)

Off-Policy Evaluation of Slate Policies under Bayes Risk. - Nikos Vlassis; Fernando Amat Gil; Ashok Chandrashekar (CoRR, 2021)

Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows. - Mahdi M. Kalayeh; Nagendra Kamath; Lingyi Liu; Ashok Chandrashekar (CoRR, 2021)

On Negative Sampling for Audio-Visual Contrastive Learning from Movies. - Mahdi M. Kalayeh; Shervin Ardeshir; Lingyi Liu; Nagendra Kamath; Ashok Chandrashekar (CoRR, 2022)

Selectively Contextual Bandits. - Claudia V. Roberts; Maria Dimakopoulou; Qifeng Qiao; Ashok Chandrashekar; Tony Jebara (CoRR, 2022)

On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks. - Claudia V. Roberts; Ehtsham Elahi; Ashok Chandrashekar (CoRR, 2022)

CLIME: Completeness-Constrained LIME. - Claudia V. Roberts; Ehtsham Elahi; Ashok Chandrashekar (WWW (Companion Volume), 2023)

Towards Understanding The Gaps of Offline And Online Evaluation Metrics: Impact of Series vs. Movie Recommendations. - Bora Edizel; Tim Sweetser; Ashok Chandrashekar; Kamilia Ahmadi; Puja Das (RecSys, 2024)