28 citations · 38 across the 3 of their papers we have counts for
3 papers
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation
Diksha Garg, Priyanka Gupta, Pankaj Malhotra +2
Most of the existing deep reinforcement learning (RL) approaches for session-based recommendations either rely on costly online interactions with real users, or rely on potentially…
NISER: Normalized Item and Session Representations to Handle Popularity Bias
Priyanka Gupta, Diksha Garg, Pankaj Malhotra +2
The goal of session-based recommendation (SR) models is to utilize the information from past actions (e.g. item/product clicks) in a session to recommend items that a user is likel…
Processing Analytical Workloads Incrementally
Priyank Gupta, Nick Koudas, Europa Shang +2
Analysis of large data collections using popular machine learning and statistical algorithms has been a topic of increasing research interest. A typical analysis workload consists…