Asish Ghoshal

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 30

Top Topics

Sample Complexity

Question Answering

Support Vector Machine

Structured Prediction

Top Venues

Publications

Minghan Li, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval. ACL (1) (2023)
Minghan Li, Sheng-Chieh Lin, Barlas Oguz, Asish Ghoshal, Jimmy Lin, Yashar Mehdad, Wen-tau Yih, Xilun Chen
CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval. CoRR (2022)
Asish Ghoshal, Arash Einolghozati, Ankit Arun, Haoran Li, Lili Yu, Yashar Mehdad, Scott Wen-tau Yih, Asli Celikyilmaz
Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences. CoRR (2022)
Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad
QUASER: Question Answering with Scalable Extractive Rationalization. SIGIR (2022)
Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, Srini Iyer
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. EMNLP (1) (2021)
Yilun Zhou, Adithya Renduchintala, Xian Li, Sida I. Wang, Yashar Mehdad, Asish Ghoshal
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms. AISTATS (2021)
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing. ICLR (2021)
Yilun Zhou, Adi Renduchintala, Xian Li, Sida I. Wang, Yashar Mehdad, Asish Ghoshal
Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms. CoRR (2021)
Kevin Bello, Asish Ghoshal, Jean Honorio
Minimax Bounds for Structured Prediction Based on Factor Graphs. AISTATS (2020)
Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing. EMNLP (1) (2020)
Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Wen-tau Yih, Yashar Mehdad, Srinivasan Iyer
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. CoRR (2020)
Xilun Chen, Asish Ghoshal, Yashar Mehdad, Luke Zettlemoyer, Sonal Gupta
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing. CoRR (2020)
Kevin Bello, Asish Ghoshal, Jean Honorio
Minimax bounds for structured prediction. CoRR (2019)
Asish Ghoshal, Jean Honorio
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time. CoRR (2018)
Asish Ghoshal, Jinyi Zhang, Michael A. Roth, Kevin Muyuan Xia, Ananth Y. Grama, Somali Chaterji
A Distributed Classifier for MicroRNA Target Prediction with Validation Through TCGA Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (4) (2018)
Asish Ghoshal, Jean Honorio
Learning linear structural equation models in polynomial time and sample complexity. AISTATS (2018)
Asish Ghoshal, Jean Honorio
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time. ICML (2018)
Asish Ghoshal, Jean Honorio
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity. AISTATS (2018)
Asish Ghoshal, Jean Honorio
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity. NIPS (2017)
Asish Ghoshal, Jean Honorio
Learning linear structural equation models in polynomial time and sample complexity. CoRR (2017)
Asish Ghoshal, Jean Honorio
Information-theoretic limits of Bayesian network structure learning. AISTATS (2017)
Asish Ghoshal, Jean Honorio
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. AISTATS (2017)
Asish Ghoshal, Jean Honorio
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. CoRR (2017)
Asish Ghoshal, Jean Honorio
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity. CoRR (2017)
Asish Ghoshal, Jean Honorio
Learning Sparse Potential Games in Polynomial Time and Sample Complexity. CoRR (2017)
Nawanol Theera-Ampornpunt, Seong Gon Kim, Asish Ghoshal, Saurabh Bagchi, Ananth Grama, Somali Chaterji
Fast training on large genomics data using distributed Support Vector Machines. COMSNETS (2016)
Asish Ghoshal, Jean Honorio
From behavior to sparse graphical games: Efficient recovery of equilibria. Allerton (2016)
Asish Ghoshal, Jean Honorio
Information-theoretic lower bounds on learning the structure of Bayesian networks. CoRR (2016)
Asish Ghoshal, Jean Honorio
From Behavior to Sparse Graphical Games: Efficient Recovery of Equilibria. CoRR (2016)
Asish Ghoshal, Ananth Grama, Saurabh Bagchi, Somali Chaterji
An ensemble SVM model for the accurate prediction of non-canonical MicroRNA targets. BCB (2015)
Asish Ghoshal, Dylan A. Shell
Covering space with simple robots: From chains to random trees. ICRA (2013)
Asish Ghoshal, Avinash Parnandi, Robin R. Murphy
Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors. PerMIS (2012)
Asish Ghoshal, Dylan A. Shell
Being There, Being the RRT: Space-Filling and Searching in Place with Minimalist Robots. AAAI Spring Symposium: Multirobot Systems and Physical Data Structures (2011)