activity
20092026
most citedVariational Autoencoders for Collaborative Filtering

64 citations · 285 across the 26 of their papers we have counts for

collaborators

28 papers

cs.IR2026

A Unified Language Model for Large Scale Search, Recommendation, and Reasoning

Marco De Nadai, Edoardo D'Amico, Max Lefarov +18

LLMs are increasingly applied to recommendation, retrieval, and reasoning, yet deploying a single end-to-end model that can jointly support these behaviors over large, heterogeneou…

cs.LG2022★ 1 cited

Selectively Contextual Bandits

Claudia Roberts, Maria Dimakopoulou, Qifeng Qiao +2

Contextual bandits are widely used in industrial personalization systems. These online learning frameworks learn a treatment assignment policy in the presence of treatment effects…

cs.LG2021★ 1 cited

Active Multitask Learning with Committees

Jingxi Xu, Da Tang, Tony Jebara

The cost of annotating training data has traditionally been a bottleneck for supervised learning approaches. The problem is further exacerbated when supervised learning is applied…

cs.LG2019

Learning Correlated Latent Representations with Adaptive Priors

Da Tang, Dawen Liang, Nicholas Ruozzi +1

Variational Auto-Encoders (VAEs) have been widely applied for learning compact, low-dimensional latent representations of high-dimensional data. When the correlation structure amon…

cs.LG2019★ 2 cited

Beta Survival Models

David Hubbard, Benoit Rostykus, Yves Raimond +1

This article analyzes the problem of estimating the time until an event occurs, also known as survival modeling. We observe through substantial experiments on large real-world data…

cs.LG2019★ 1 cited

A New Distribution on the Simplex with Auto-Encoding Applications

Andrew Stirn, Tony Jebara, David A Knowles

We construct a new distribution for the simplex using the Kumaraswamy distribution and an ordered stick-breaking process. We explore and develop the theoretical properties of this…