64 citations · 285 across the 26 of their papers we have counts for
16 papers · 1 filter
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…
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…
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…
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…
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…
Correlated Variational Auto-Encoders
Da Tang, Dawen Liang, Tony Jebara +1
Variational Auto-Encoders (VAEs) are capable of learning latent representations for high dimensional data. However, due to the i.i.d. assumption, VAEs only optimize the singleton v…