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Dinesh Garg
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2020 – today
- 2024
- [c43]Prince Kumar, Srikanth Tamilselvam, Dinesh Garg:
Read between the lines - Functionality Extraction From READMEs. NAACL-HLT (Findings) 2024: 3977-3990 - [i19]Prince Kumar, Srikanth Tamilselvam, Dinesh Garg:
Read between the lines - Functionality Extraction From READMEs. CoRR abs/2403.10205 (2024) - [i18]G. P. Shrivatsa Bhargav, Sumit Neelam, Udit Sharma, Shajith Ikbal, Dheeraj Sreedhar, Hima Karanam, Sachindra Joshi, Pankaj Dhoolia, Dinesh Garg, Kyle Croutwater, Haode Qi, Eric Wayne, J. William Murdock:
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants. CoRR abs/2406.08848 (2024) - 2023
- [c42]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Ashish Goswami, Satyam Modi, Arnab Kumar Mondal, Dinesh Khandelwal, Dinesh Garg, Parag Singla:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. EMNLP 2023: 2975-3007 - [i17]Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla, Dinesh Garg:
Image Manipulation via Multi-Hop Instructions - A New Dataset and Weakly-Supervised Neuro-Symbolic Approach. CoRR abs/2305.14410 (2023) - [i16]Aniruddha Deb, Neeva Oza, Sarthak Singla, Dinesh Khandelwal, Dinesh Garg, Parag Singla:
Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems. CoRR abs/2310.01991 (2023) - 2022
- [c41]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases. EMNLP (Findings) 2022: 3866-3879 - [c40]Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav:
A Deep Neural Approach to KGQA via SPARQL Silhouette Generation. IJCNN 2022: 1-8 - [c39]Sumit Negi, Manisha Verma, Rajdeep H. Banerjee, Pooja A, Lydia B. Chilton, Mithun Das Gupta, Vinay P. Namboodiri, Dinesh Garg:
First Workshop on Content Understanding and Generation for E-commerce. KDD 2022: 4888-4889 - [c38]G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Saswati Dana, Dinesh Garg, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray, L. Venkata Subramaniam:
Zero-shot Entity Linking with Less Data. NAACL-HLT (Findings) 2022: 1681-1697 - [i15]Philip Tetlow, Dinesh Garg, Leigh Chase, Mark Mattingley-Scott, Nicholas Bronn, Kugendran Naidoo, Emil Reinert:
Towards a Semantic Information Theory (Introducing Quantum Corollas). CoRR abs/2201.05478 (2022) - [i14]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases. CoRR abs/2201.05793 (2022) - 2021
- [c37]Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg:
Explanations for CommonsenseQA: New Dataset and Models. ACL/IJCNLP (1) 2021: 3050-3065 - [c36]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering. ACL/IJCNLP (Findings) 2021: 3884-3894 - [c35]Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar:
Deep Domain Adaptation under Label Scarcity. COMAD/CODS 2021: 101-109 - [c34]G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Dinesh Garg, Saswati Dana:
Semantic Answer Type Prediction. SMART@ISWC 2021: 14-22 - [i13]Sukannya Purkayastha, Saswati Dana, Dinesh Garg, Dinesh Khandelwal, G. P. Shrivatsa Bhargav:
Knowledge Graph Question Answering via SPARQL Silhouette Generation. CoRR abs/2109.09475 (2021) - [i12]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases. CoRR abs/2109.13430 (2021) - 2020
- [c33]G. P. Shrivatsa Bhargav, Michael R. Glass, Dinesh Garg, Shirish K. Shevade, Saswati Dana, Dinesh Khandelwal, L. Venkata Subramaniam, Alfio Gliozzo:
Translucent Answer Predictions in Multi-Hop Reading Comprehension. AAAI 2020: 7700-7707 - [c32]Vittorio Castelli, Rishav Chakravarti, Saswati Dana, Anthony Ferritto, Radu Florian, Martin Franz, Dinesh Garg, Dinesh Khandelwal, J. Scott McCarley, Mike McCawley, Mohamed Nasr, Lin Pan, Cezar Pendus, John F. Pitrelli, Saurabh Pujar, Salim Roukos, Andrzej Sakrajda, Avirup Sil, Rosario Uceda-Sosa, Todd Ward, Rong Zhang:
The TechQA Dataset. ACL 2020: 1269-1278 - [c31]Michael R. Glass, Alfio Gliozzo
, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil:
Span Selection Pre-training for Question Answering. ACL 2020: 2773-2782 - [c30]Santosh K. Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam, L. Venkata Subramaniam:
Inductive Quantum Embedding. NeurIPS 2020 - [i11]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning. CoRR abs/2012.01707 (2020)
2010 – 2019
- 2019
- [j7]Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
Improved linear embeddings via Lagrange duality. Mach. Learn. 108(4): 575-594 (2019) - [c29]Dinesh Garg, Shajith Ikbal, Santosh K. Srivastava, Harit Vishwakarma, Hima P. Karanam, L. Venkata Subramaniam:
Quantum Embedding of Knowledge for Reasoning. NeurIPS 2019: 5595-5605 - [i10]Richa Tripathi, Amit Reza, Dinesh Garg:
Prediction of the disease controllability in a complex network using machine learning algorithms. CoRR abs/1902.10224 (2019) - [i9]Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, Avirup Sil:
Span Selection Pre-training for Question Answering. CoRR abs/1909.04120 (2019) - [i8]Vittorio Castelli, Rishav Chakravarti, Saswati Dana, Anthony Ferritto, Radu Florian, Martin Franz, Dinesh Garg, Dinesh Khandelwal, J. Scott McCarley, Mike McCawley, Mohamed Nasr, Lin Pan, Cezar Pendus, John F. Pitrelli, Saurabh Pujar, Salim Roukos, Andrzej Sakrajda, Avirup Sil, Rosario Uceda-Sosa, Todd Ward, Rong Zhang:
The TechQA Dataset. CoRR abs/1911.02984 (2019) - 2018
- [i7]Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal, Arun Kumar:
Deep Domain Adaptation under Deep Label Scarcity. CoRR abs/1809.08097 (2018) - 2017
- [c28]Deepak P
Latent Space Embedding for Retrieval in Question-Answer Archives. EMNLP 2017: 855-865 - [c27]Rohit Vaish, Dinesh Garg:
Manipulating Gale-Shapley Algorithm: Preserving Stability and Remaining Inconspicuous. IJCAI 2017: 437-443 - [c26]Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg:
A Sparse Nonlinear Classifier Design Using AUC Optimization. SDM 2017: 291-299 - [i6]Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta:
Improved Linear Embeddings via Lagrange Duality. CoRR abs/1711.11527 (2017) - 2016
- [j6]Alankar Jain, Vivek S. Borkar, Dinesh Garg:
Fast rumor source identification via random walks. Soc. Netw. Anal. Min. 6(1): 62:1-62:13 (2016) - [c25]Ashish Bora, Vivek S. Borkar, Dinesh Garg, Rajesh Sundaresan:
Edge conductance estimation using MCMC. Allerton 2016: 202-208 - [c24]Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari:
A Robust UCB scheme for active learning in regression from strategic crowds. IJCNN 2016: 2212-2219 - [i5]Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish K. Shevade, Y. Narahari:
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds. CoRR abs/1601.06750 (2016) - [i4]Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg:
A Sparse Nonlinear Classifier Design Using AUC Optimization. CoRR abs/1612.08633 (2016) - 2015
- [c23]Pankaj Dayama, Balakrishnan Narayanaswamy, Dinesh Garg, Y. Narahari:
Truthful Interval Cover Mechanisms for Crowdsourcing Applications. AAMAS 2015: 1091-1099 - 2014
- [c22]Rakesh Pimplikar, Dinesh Garg, Deepesh Bharani, Gyana R. Parija:
Learning to Propagate Rare Labels. CIKM 2014: 201-210 - [c21]Ramasuri Narayanam, Dinesh Garg, Hemank Lamba:
Discovering signature of social networks with application to community detection. COMSNETS 2014: 1-7 - [c20]Avradeep Bhowmik, Vivek S. Borkar, Dinesh Garg, Madhavan Pallan:
Submodularity in Team Formation Problem. SDM 2014: 893-901 - [i3]Gugan Thoppe, Vivek S. Borkar, Dinesh Garg:
An Improved Block Coordinate Descent Method for Quadratic Programming in High Dimensions. CoRR abs/1404.6635 (2014) - 2012
- [c19]Swaprava Nath, Pankaj Dayama, Dinesh Garg, Y. Narahari, James Y. Zou:
Threats and Trade-Offs in Resource Critical Crowdsourcing Tasks Over Networks. AAAI 2012: 2447-2448 - [c18]Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade:
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. UAI 2012: 275-285 - [c17]Swaprava Nath
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. WINE 2012: 212-226 - [i2]Swaprava Nath
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing. CoRR abs/1208.1676 (2012) - [i1]Dinesh Garg, Sourangshu Bhattacharya, S. Sundararajan, Shirish K. Shevade:
Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. CoRR abs/1210.4859 (2012) - 2011
- [c16]Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade:
A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. PAKDD (1) 2011: 13-25 - [c15]Michael Grabchak, Narayan L. Bhamidipati, Rushi Bhatt, Dinesh Garg:
Adaptive policies for selecting groupon style chunked reward ads in a stochastic knapsack framework. WWW 2011: 167-176
2000 – 2009
- 2009
- [b1]Y. Narahari, Dinesh Garg, Ramasuri Narayanam, V. Hastagiri Prakash:
Game Theoretic Problems in Network Economics and Mechanism Design Solutions. Advanced Information and Knowledge Processing, Springer 2009, ISBN 978-1-84800-937-0, pp. 1-274 - [j5]Dinesh Garg, Y. Narahari:
An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms. IEEE Trans Autom. Sci. Eng. 6(4): 641-657 (2009) - [c14]Lakshmish Ramaswamy, P. Deepak, Ramana Polavarapu, Kutila Gunasekera, Dinesh Garg, Karthik Visweswariah, Shivkumar Kalyanaraman:
CAESAR: A Context-Aware, Social Recommender System for Low-End Mobile Devices. Mobile Data Management 2009: 338-347 - [c13]Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari:
Nash Bargaining Based Ad Networks for Sponsored Search Auctions. CEC 2009: 170-175 - 2008
- [j4]Dinesh Garg, Y. Narahari:
Mechanism Design for Single Leader Stackelberg Problems and Application to Procurement Auction Design. IEEE Trans Autom. Sci. Eng. 5(3): 377-393 (2008) - [c12]Prasad M. Deshpande, Dinesh Garg, Ramasuri Narayanam:
Auction Based Models for Ticket Allocation Problem in IT Service Delivery Industry. IEEE SCC (1) 2008: 111-118 - [c11]Dinesh Garg, Nanda Kambhatla, Maja Vukovic, Gopal Pingali:
Mining Top Issues from Contact Center Logs for Self Help Portals. IEEE SCC (2) 2008: 171-178 - [c10]Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Yadati Narahari:
A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids. CASE 2008: 1007-1012 - 2007
- [j3]Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani:
A primal-dual algorithm for computing Fisher equilibrium in the absence of gross substitutability property. Theor. Comput. Sci. 378(2): 143-152 (2007) - [c9]Zon-Yin Shae, Dinesh Garg, Rajarshi Bhose, Ritabrata Mukherjee, Sinem Güven:
Efficient Internet Chat Services for Help Desk Agents. IEEE SCC 2007: 589-596 - [c8]Dinesh Garg, Y. Narahari, Siva Sankar Reddy:
Design of an Optimal Auction for Sponsored Search Auction. CEC/EEE 2007: 439-442 - 2006
- [j2]Dinesh Garg, Y. Narahari, Nukala Viswanadham:
Achieving sharp deliveries in supply chains through variance pool allocation. Eur. J. Oper. Res. 171(1): 227-254 (2006) - 2005
- [c7]Dinesh Garg, Yadati Narahari, Earnest Foster, Devadatta M. Kulkarni, Jeffrey D. Tew:
A Groves Mechanism Approach to Decentralized Design of Supply Chains. CEC 2005: 330-337 - [c6]Dinesh Garg, Kamal Jain, Kunal Talwar, Vijay V. Vazirani:
A Primal-Dual Algorithm for Computing Fisher Equilibrium in the Absence of Gross Substitutability Property. WINE 2005: 24-33 - [c5]Dinesh Garg, Yadati Narahari:
Design of Incentive Compatible Mechanisms for Stackelberg Problems. WINE 2005: 718-727 - [c4]Dinesh Garg, Yadati Narahari:
Price of Anarchy of Network Routing Games with Incomplete Information. WINE 2005: 1066-1075 - 2004
- [j1]Dinesh Garg, Yadati Narahari, Nukala Viswanadham:
Design of six sigma supply chains. IEEE Trans Autom. Sci. Eng. 1(1): 38-57 (2004) - 2003
- [c3]Dinesh Garg, Yadati Narahari, Nukala Viswanadham:
Design of six sigma supply chains. ICRA 2003: 1737-1742 - [c2]Dinesh Garg, Yadati Narahari, Nukala Viswanadham:
A new approach to achieving sharp and timely deliveries in supply chain networks. IROS 2003: 2315-2320 - 2002
- [c1]Dinesh Garg, Yadati Narahari, Nukala Viswanadham:
Achieving Sharp Deliveries in Supply Chains through Variance Pool Allocation. ICRA 2002: 2345-2350
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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