178 citations · 289 across the 10 of their papers we have counts for
12 papers
DeLoop: Repeated Actions as Self-Supervision for Long-Horizon Agents
Tianle Chen, Pushkar Singh, Ketan Todi +8
Language-model agents that run long tasks often redo work they have already done: they re-issue a tool call they made earlier and get back exactly the same observation, a step that…
Gradient-Based Constrained Sampling from Language Models
Sachin Kumar, Biswajit Paria, Yulia Tsvetkov
Large pretrained language models generate fluent text but are notoriously hard to controllably sample from. In this work, we study constrained sampling from such language models: g…
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting
Abhimanyu Das, Weihao Kong, Biswajit Paria +1
Probabilistic, hierarchically coherent forecasting is a key problem in many practical forecasting applications -- the goal is to obtain coherent probabilistic predictions for a lar…
An Experimental Design Perspective on Model-Based Reinforcement Learning
Viraj Mehta, Biswajit Paria, Jeff Schneider +2
In many practical applications of RL, it is expensive to observe state transitions from the environment. For example, in the problem of plasma control for nuclear fusion, computing…
Hierarchically Regularized Deep Forecasting
Biswajit Paria, Rajat Sen, Amr Ahmed +1
Hierarchical forecasting is a key problem in many practical multivariate forecasting applications - the goal is to simultaneously predict a large number of correlated time series t…
Minimizing FLOPs to Learn Efficient Sparse Representations
Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen +3
Deep representation learning has become one of the most widely adopted approaches for visual search, recommendation, and identification. Retrieval of such representations from a la…
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning
Adarsh Dave, Jared Mitchell, Kirthevasan Kandasamy +5
Innovations in batteries take years to formulate and commercialize, requiring extensive experimentation during the design and optimization phases. We approached the design and sele…
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger +5
Bayesian Optimisation (BO) refers to a suite of techniques for global optimisation of expensive black box functions, which use introspective Bayesian models of the function to effi…
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations
Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
Many real world applications can be framed as multi-objective optimization problems, where we wish to simultaneously optimize for multiple criteria. Bayesian optimization technique…
Analytic Connectivity in General Hypergraphs
Ashwin Guha, Muni Sreenivas Pydi, Biswajit Paria +1
In this paper we extend the known results of analytic connectivity to non-uniform hypergraphs. We prove a modified Cheeger's inequality and also give a bound on analytic connectivi…
A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference
Biswajit Paria, K. M. Annervaz, Ambedkar Dukkipati +2
In this work we use the recent advances in representation learning to propose a neural architecture for the problem of natural language inference. Our approach is aligned to mimic…
Forward Stagewise Additive Model for Collaborative Multiview Boosting
Avisek Lahiri, Biswajit Paria, Prabir Kumar Biswas
Multiview assisted learning has gained significant attention in recent years in supervised learning genre. Availability of high performance computing devices enables learning algor…