Pairwise Preferences Based Matrix Factorization and Nearest Neighbor Recommendation Techniques. - Saikishore Kalloori; Francesco Ricci 001; Marko Tkalcic (RecSys, 2016)

Pairwise Preferences and Recommender Systems. - Saikishore Kalloori (IUI Companion, 2017)

Improving Cold Start Recommendation by Mapping Feature-Based Preferences to Item Comparisons. - Saikishore Kalloori; Francesco Ricci 001 (UMAP, 2017)

Integrating Ratings and Pairwise Preferences in Recommender Systems. - Saikishore Kalloori; Francesco Ricci 001 (IIR, 2018)

Eliciting pairwise preferences in recommender systems. - Saikishore Kalloori; Francesco Ricci 001; Rosella Gennari (RecSys, 2018)

Item Recommendation by Combining Relative and Absolute Feedback Data. - Saikishore Kalloori; Tianyu Li; Francesco Ricci 001 (SIGIR, 2019)

Modeling User Preferences Using Relative Feedback for Personalized Recommendations. - Saikishore Kalloori; Tianyu Li (FLAIRS, 2020)

RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter's Home Timeline. - Vito Walter Anelli; Saikishore Kalloori; Bruce Ferwerda; Luca Belli; Alykhan Tejani; Frank Portman; Alexandre Lung-Yut-Fong; Ben Chamberlain 001; Yuanpu Xie; Jonathan Hunt; Michael M. Bronstein; Wenzhe Shi (RecSys, 2021)

The 2021 RecSys Challenge Dataset: Fairness is not optional. - Luca Belli; Alykhan Tejani; Frank Portman; Alexandre Lung-Yut-Fong; Ben Chamberlain 001; Yuanpu Xie; Kristian Lum; Jonathan Hunt; Michael M. Bronstein; Vito Walter Anelli; Saikishore Kalloori; Bruce Ferwerda; et al. (RecSys Challenge, 2021)

Horizontal Cross-Silo Federated Recommender Systems. - Saikishore Kalloori; Severin Klingler (RecSys, 2021)

A Practical Federated Learning Framework for Small Number of Stakeholders. - Christian Schneebeli; Saikishore Kalloori; Severin Klingler (WSDM, 2021)

Fast Content Placement and Alignment in 3D Scenes. - Robin Wiethüchter; Saikishore Kalloori; Ribin Chalumattu (FLAIRS, 2022)

RecSys Challenge 2022: Fashion Purchase Prediction. - Nick Landia; Frederick Cheung; Donna North; Saikishore Kalloori; Abhishek Srivastava 004; Bruce Ferwerda (RecSys, 2022)

Cross-silo federated learning based decision trees. - Saikishore Kalloori; Severin Klingler (SAC, 2022)

Personalized Information Retrieval for Touristic Attractions in Augmented Reality. - Felix Yang; Saikishore Kalloori; Ribin Chalumattu; Markus Gross 001 (WSDM, 2022)

RecSys Challenge 2023 Dataset: Ads Recommendations in Online Advertising. - Rahul Agrawal; Sarang Brahme; Sourav Maitra; Abhishek Srivastava 004; Athirai A. Irissappane; Yong Liu 020; Saikishore Kalloori (RecSys Challenge, 2023)

RecSys Challenge 2023: Deep Funnel Optimization with a Focus on User Privacy. - Rahul Agrawal; Sarang Brahme; Sourav Maitra; Saikishore Kalloori; Abhishek Srivastava 004; Yong Liu 020; Athirai A. Irissappane (RecSys, 2023)

A Retrieval System for Images and Videos based on Aesthetic Assessment of Visuals. - Daniel Vera Nieto; Saikishore Kalloori; Fabio Zund; Clara Fernandez-Labrador; Marc Willhaus; Severin Klingler; Markus Gross 001 (SIGIR, 2023)

Improving German News Clustering with Contrastive Learning. - Piriyakorn Piriyatamwong; Saikishore Kalloori; Fabio Zünd (CIKM, 2024)

Unified Argument Retrieval System from German News Articles Using Large Language Models. - Piriyakorn Piriyatamwong; Saikishore Kalloori; Fabio Zünd (CIKM, 2024)

Federated Learning for Cold Start Recommendations. - Saikishore Kalloori (COMAD/CODS, 2024)

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations. - Johannes Kruse 002; Kasper Lindskow; Saikishore Kalloori; Marco Polignano; Claudio Pomo; Abhishek Srivastava 004; Anshuk Uppal; Michael Riis Andersen; Jes Frellsen (RecSys, 2024)

EB-NeRD a large-scale dataset for news recommendation. - Johannes Kruse 002; Kasper Lindskow; Saikishore Kalloori; Marco Polignano; Claudio Pomo; Abhishek Srivastava 004; Anshuk Uppal; Michael Riis Andersen; Jes Frellsen (RecSys Challenge, 2024)

Balancing Autonomy: Investigating User-Controlled vs Automated Guidance Systems for Sequential Tasks. - Robin Wiethüchter; Saikishore Kalloori; David Lindlbauer (ISS Companion, 2024)

Side-By-Side Might Win: Occlusion Negatively Affects The Performance Of Augmented Reality Task Instructions. - Robin Wiethüchter; Saikishore Kalloori; David Lindlbauer (VR Workshops, 2024)

Towards cross-silo federated learning for corporate organizations. - Saikishore Kalloori; Abhishek Srivastava 004 (Knowl. Based Syst., 2024)