1.6k citations · 5.9k across the 67 of their papers we have counts for
67 papers
Deep Explicit Duration Switching Models for Time Series
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle +5
Many complex time series can be effectively subdivided into distinct regimes that exhibit persistent dynamics. Discovering the switching behavior and the statistical patterns in th…
IRLI: Iterative Re-partitioning for Learning to Index
Gaurav Gupta, Tharun Medini, Anshumali Shrivastava +1
Neural models have transformed the fundamental information retrieval problem of mapping a query to a giant set of items. However, the need for efficient and low latency inference f…
Continuous Doubly Constrained Batch Reinforcement Learning
Rasool Fakoor, Jonas Mueller, Kavosh Asadi +2
Reliant on too many experiments to learn good actions, current Reinforcement Learning (RL) algorithms have limited applicability in real-world settings, which can be too expensive…
Bloom Origami Assays: Practical Group Testing
Louis Abraham, Gary Becigneul, Benjamin Coleman +3
We study the problem usually referred to as group testing in the context of COVID-19. Given n samples collected from patients, how should we select and test mixtures of samples to…
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph
Jiarui Jin, Jiarui Qin, Yuchen Fang +5
There is an influx of heterogeneous information network (HIN) based recommender systems in recent years since HIN is capable of characterizing complex graphs and contains rich sema…
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
This paper prescribes a suite of techniques for off-policy Reinforcement Learning (RL) that simplify the training process and reduce the sample complexity. First, we show that simp…