6 papers
GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation
Krishna Acharya, Aleksandr V. Petrov, Juba Ziani
We propose Generative Low-rank language model with Semantic Search (GLoSS), a generative recommendation framework that combines large language models with dense retrieval for seque…
Last-iterate Convergence for Symmetric, General-sum, Games Under The Exponential Weights Dynamic
Guanghui Wang, Krishna Acharya, Lokranjan Lakshmikanthan +2
We conduct a comprehensive analysis of the discrete-time exponential-weights dynamic with a constant step size on all general-sum and symmetric normal-form games, i.e.…
Improving Minimax Group Fairness in Sequential Recommendation
Krishna Acharya, David Wardrope, Timos Korres +2
Training sequential recommenders such as SASRec with uniform sample weights achieves good overall performance but can fall short on specific user groups. One such example is popula…
Personalized Differential Privacy for Ridge Regression
Krishna Acharya, Franziska Boenisch, Rakshit Naidu +1
The increased application of machine learning (ML) in sensitive domains requires protecting the training data through privacy frameworks, such as differential privacy (DP). DP requ…
Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems
Krishna Acharya, Varun Vangala, Jingyan Wang +1
Online platforms such as YouTube, Instagram heavily rely on recommender systems to decide what content to present to users. Producers, in turn, often create content that is likely…
Oracle Efficient Algorithms for Groupwise Regret
Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan +2
We study the problem of online prediction, in which at each time step , an individual arrives, whose label we must predict. Each individual is associated with various grou…