254 citations · 384 across the 9 of their papers we have counts for
9 papers
Online Heavy-tailed Change-point detection
Abishek Sankararaman, Balakrishnan, Narayanaswamy
We study algorithms for online change-point detection (OCPD), where samples that are potentially heavy-tailed, are presented one at a time and a change in the underlying mean must…
Predict-and-Critic: Accelerated End-to-End Predictive Control for Cloud Computing through Reinforcement Learning
Kaustubh Sridhar, Vikramank Singh, Balakrishnan Narayanaswamy +1
Cloud computing holds the promise of reduced costs through economies of scale. To realize this promise, cloud computing vendors typically solve sequential resource allocation probl…
Zero-Shot Learning for Joint Intent and Slot Labeling
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy
It is expensive and difficult to obtain the large number of sentence-level intent and token-level slot label annotations required to train neural network (NN)-based Natural Languag…
ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problems
Bharathan Balaji, Jordan Bell-Masterson, Enes Bilgin +7
Reinforcement Learning (RL) has achieved state-of-the-art results in domains such as robotics and games. We build on this previous work by applying RL algorithms to a selection of…
Imitation-Regularized Offline Learning
Yifei Ma, Yu-Xiang Wang, Balakrishnan +1
We study the problem of offline learning in automated decision systems under the contextual bandits model. We are given logged historical data consisting of contexts, (randomized)…
Achieving Fluency and Coherency in Task-oriented Dialog
Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan
We consider real world task-oriented dialog settings, where agents need to generate both fluent natural language responses and correct external actions like database queries and up…
A Multi-Horizon Quantile Recurrent Forecaster
Ruofeng Wen, Kari Torkkola, Balakrishnan Narayanaswamy +1
We propose a framework for general probabilistic multi-step time series regression. Specifically, we exploit the expressiveness and temporal nature of Sequence-to-Sequence Neural N…
Thresholding Classifiers to Maximize F1 Score
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
This paper provides new insight into maximizing F1 scores in the context of binary classification and also in the context of multilabel classification. The harmonic mean of precisi…
Game Theoretic Analysis of Production-Management Effort Distribution in Organizational Networks
Swaprava Nath, Balakrishnan, Narayanaswamy
Organizations consist of individuals connected by their responsibilities, incentives, and reporting structure. These connections are aptly represented by a network, hierarchical or…