Asish Ghoshal

34 papers A* 4A 7Misc 1Journal 14Unranked 8
YearRankTypeTitle / Venue / Authors
2024 A conf
Identifying Causal Changes Between Linear Structural Equation Models.
UAI
Vineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio
2023 — conf
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval.
ACL (1)
Minghan Li, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen
2022 J jnl
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval.
CoRR
Minghan Li, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen
2022 J jnl
Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences.
CoRR
Asish Ghoshal, Arash Einolghozati, Ankit Arun, Haoran Li, Lili Yu, Yashar Mehdad, Scott Wen-tau Yih, Asli Celikyilmaz
2022 A* conf
QUASER: Question Answering with Scalable Extractive Rationalization.
SIGIR
Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad
2021 — conf
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation.
EMNLP (1)
Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, Srini Iyer
2021 A* conf
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing.
ICLR
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
2021 A conf
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms.
AISTATS
Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal
2021 J jnl
Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms.
CoRR
Yilun Zhou, Adi Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal
2020 J jnl
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation.
CoRR
Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Wen-tau Yih, Yashar Mehdad, Srinivasan Iyer
2020 — conf
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing.
EMNLP (1)
Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta
2020 J jnl
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing.
CoRR
Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta
2020 A conf
Minimax Bounds for Structured Prediction Based on Factor Graphs.
AISTATS
Kevin Bello, Asish Ghoshal, Jean Honorio
2019 J jnl
Minimax bounds for structured prediction.
CoRR
Kevin Bello, Asish Ghoshal, Jean Honorio
2018 J jnl
A Distributed Classifier for MicroRNA Target Prediction with Validation Through TCGA Expression Data.
IEEE ACM Trans. Comput. Biol. Bioinform.
Asish Ghoshal, Jinyi Zhang, Michael A. Roth, Kevin Muyuan Xia, Ananth Y. Grama, Somali Chaterji
2018 A* conf
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time.
ICML
Asish Ghoshal, Jean Honorio
2018 J jnl
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time.
CoRR
Asish Ghoshal, Jean Honorio
2018 A conf
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity.
AISTATS
Asish Ghoshal, Jean Honorio
2018 A conf
Learning linear structural equation models in polynomial time and sample complexity.
AISTATS
Asish Ghoshal, Jean Honorio
2017 A conf
Information-theoretic limits of Bayesian network structure learning.
AISTATS
Asish Ghoshal, Jean Honorio
2017 A conf
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions.
AISTATS
Asish Ghoshal, Jean Honorio
2017 J jnl
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions.
CoRR
Asish Ghoshal, Jean Honorio
2017 — conf
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity.
NIPS
Asish Ghoshal, Jean Honorio
2017 J jnl
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity.
CoRR
Asish Ghoshal, Jean Honorio
2017 J jnl
Learning Sparse Potential Games in Polynomial Time and Sample Complexity.
CoRR
Asish Ghoshal, Jean Honorio
2017 J jnl
Learning linear structural equation models in polynomial time and sample complexity.
CoRR
Asish Ghoshal, Jean Honorio
2016 Misc conf
Fast training on large genomics data using distributed Support Vector Machines.
COMSNETS
Nawanol Theera-Ampornpunt, Seong Gon Kim, Asish Ghoshal, Saurabh Bagchi, Ananth Grama, Somali Chaterji
2016 J jnl
From Behavior to Sparse Graphical Games: Efficient Recovery of Equilibria.
CoRR
Asish Ghoshal, Jean Honorio
2016 — conf
From behavior to sparse graphical games: Efficient recovery of equilibria.
Allerton
Asish Ghoshal, Jean Honorio
2016 J jnl
Information-theoretic lower bounds on learning the structure of Bayesian networks.
CoRR
Asish Ghoshal, Jean Honorio
2015 — conf
An ensemble SVM model for the accurate prediction of non-canonical MicroRNA targets.
BCB
Asish Ghoshal, Ananth Grama, Saurabh Bagchi, Somali Chaterji
2013 A* conf
Covering space with simple robots: From chains to random trees.
ICRA
Asish Ghoshal, Dylan A. Shell
2012 — conf
Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors.
PerMIS
Asish Ghoshal, Avinash Parnandi, Robin R. Murphy
2011 — conf
Being There, Being the RRT: Space-Filling and Searching in Place with Minimalist Robots.
AAAI Spring Symposium: Multirobot Systems and Physical Data Structures
Asish Ghoshal, Dylan A. Shell