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Nisheeth Srivastava
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2020 – today
- 2023
- [c48]Shubhamkar Ayare, Nisheeth Srivastava:
Tracking Multiple Objects without Indexes. CogSci 2023 - [c47]Pritam Laskar, Nisheeth Srivastava:
Groups are Better than Individuals at Solving Optimum Stopping Problems. CogSci 2023 - [c46]Samarth Mehrotra, Nisheeth Srivastava:
Measuring the time utility of mental effort. CogSci 2023 - [c45]Arjun Mitra, Nisheeth Srivastava, Narayanan Srinivasan:
Unpredictability shortens planning horizons. CogSci 2023 - [c44]Revati Vijay Shivnekar, Nisheeth Srivastava:
Measuring Moral Vacillations. CogSci 2023 - [c43]Anjali Sifar, Hariharan Purohit, Nisheeth Srivastava:
Measuring the completeness of race models for perceptual decision-making. CogSci 2023 - [c42]Abhishek Jaiswal
, Gautam Chauhan
, Nisheeth Srivastava
:
Using Learnable Physics for Real-Time Exercise Form Recommendations. RecSys 2023: 688-695 - [c41]Pratyush Arya, Nisheeth Srivastava
:
Understanding Clique Formation in Social Networks - An Agent-Based Model of Social Preferences in Fixed and Dynamic Networks. SBP-BRiMS 2023: 231-240 - [i5]Abhishek Jaiswal, Gautam Chauhan, Nisheeth Srivastava:
Using Learnable Physics for Real-Time Exercise Form Recommendations. CoRR abs/2310.07221 (2023) - 2022
- [c40]Bhanu Prakash Ankoju, Nisheeth Srivastava:
Sampling-based probability construction explains individual differences in risk preference. CogSci 2022 - [c39]Samarth Mehrotra, Nisheeth Srivastava:
Selecting between visuomotor lotteries to measure mental effort in risky decisions. CogSci 2022 - 2021
- [c38]Sharad Shukla, Nisheeth Srivastava:
Federated matched averaging with information-gain based parameter sampling. AIMLSystems 2021: 5:1-5:7 - [c37]Shobhit Jagga, Narayanan Srinivasan, Nisheeth Srivastava:
Modeling procrastination as rational metareasoning about task effort. CogSci 2021 - [c36]Ishan Singhal, Narayanan Srinivasan, Nisheeth Srivastava:
One and known: Incidental probability judgments from very few samples. CogSci 2021 - [c35]Anjali Sifar, Nisheeth Srivastava:
Imprecise Oracles Impose Limits to Predictability in Supervised Learning (Extended Abstract). IJCAI 2021: 4834-4838 - 2020
- [c34]Harish Balakrishnan, Shobhit Jagga, Nisheeth Srivastava:
Inducing preference reversals by manipulating revealed preferences. CogSci 2020 - [c33]Anjali Sifar, Nisheeth Srivastava:
Limits on Predictability of Risky Choice Behavior. CogSci 2020 - [c32]Umair Z. Ahmed, Nisheeth Srivastava, Renuka Sindhgatta, Amey Karkare
:
Characterizing the pedagogical benefits of adaptive feedback for compilation errors by novice programmers. ICSE (SEET) 2020: 139-150 - [c31]Jatin Aswal, Nisheeth Srivastava:
A Recommender System for Informal Bibliotherapy. HealthRecSys@RecSys 2020: 23-27 - [c30]Tushar Shandhilya, Nisheeth Srivastava:
Using conceptual incongruity as a basis for making recommendations. RecSys 2020: 557-561
2010 – 2019
- 2019
- [c29]Nisheeth Srivastava:
Evidence for effort prediction in perceptual decisions. CogSci 2019: 2852-2857 - [c28]Nisheeth Srivastava:
Decision-makers minimize regret when calculating regret is easy. CogSci 2019: 2858-2863 - [c27]Arjun Mitra, Narayanan Srinivasan, Nisheeth Srivastava:
Planning failures induced by budgetary overruns cause intertemporal impulsivity. CogSci 2019: 3319 - [c26]Meet Sheth, Nisheeth Srivastava:
Predicting Body Size Using Mirror Selfies. IHCI 2019: 151-162 - [c25]Umair Z. Ahmed, Renuka Sindhgatta
, Nisheeth Srivastava, Amey Karkare
:
Targeted Example Generation for Compilation Errors. ASE 2019: 327-338 - [c24]Homanga Bharadhwaj, Nisheeth Srivastava:
New Tab Page Recommendations Strongly Concentrate Web Browsing to Familiar Sources. WebSci 2019: 7-16 - [i4]Umair Z. Ahmed, Renuka Sindhgatta, Nisheeth Srivastava, Amey Karkare:
Targeted Example Generation for Compilation Errors. CoRR abs/1909.00769 (2019) - 2018
- [j3]Jeenath Rahaman, Harshit Agrawal, Nisheeth Srivastava, Sanjay Chandrasekharan:
Recombinant Enaction: Manipulatives Generate New Procedures in the Imagination, by Extending and Recombining Action Spaces. Cogn. Sci. 42(2): 370-415 (2018) - [c23]Nisheeth Srivastava
:
Measuring Conceptual Incongruity from Text-Based Annotations. IHCI 2018: 161-169 - [c22]Daniel Firestone, Andrew Putnam, Sambrama Mundkur, Derek Chiou, Alireza Dabagh, Mike Andrewartha, Hari Angepat, Vivek Bhanu, Adrian M. Caulfield, Eric S. Chung, Harish Kumar Chandrappa, Somesh Chaturmohta, Matt Humphrey, Jack Lavier, Norman Lam, Fengfen Liu, Kalin Ovtcharov, Jitu Padhye, Gautham Popuri, Shachar Raindel, Tejas Sapre, Mark Shaw, Gabriel Silva, Madhan Sivakumar, Nisheeth Srivastava, Anshuman Verma, Qasim Zuhair, Deepak Bansal, Doug Burger, Kushagra Vaid, David A. Maltz, Albert G. Greenberg:
Azure Accelerated Networking: SmartNICs in the Public Cloud. NSDI 2018: 51-66 - [i3]Archit Sakhadeo, Nisheeth Srivastava:
Effective extractive summarization using frequency-filtered entity relationship graphs. CoRR abs/1810.10419 (2018) - [i2]Homanga Bharadhwaj, Nisheeth Srivastava:
New tab page recommendations cause a strong suppression of exploratory web browsing behaviors. CoRR abs/1812.06525 (2018) - 2017
- [c21]Nisheeth Srivastava:
Memory of relative magnitude judgments informs absolute identification. CogSci 2017 - [c20]Nisheeth Srivastava, Ed Vul:
A rational analysis of marketing strategies. CogSci 2017 - [c19]Nisheeth Srivastava, Ed Vul:
Rationalizing subjective probability distortions. CogSci 2017 - [c18]Nisheeth Srivastava, Edward Vul:
A simple model of recognition and recall memory. NIPS 2017: 293-301 - 2016
- [j2]Nisheeth Srivastava, Ed Vul:
Attention Modulates Spatial Precision in Multiple-Object Tracking. Top. Cogn. Sci. 8(1): 335-348 (2016) - [c17]Nisheeth Srivastava, Johannes Müller-Trede, Paul R. Schrater, Edward Vul:
Modeling sampling duration in decisions from experience. CogSci 2016 - 2015
- [c16]Sanjay Chandrasekharan, Geetanjali Date, Prajakt Pande, Jeenath Rahaman, Rafikh Shaikh, Anveshna Srivastava, Nisheeth Srivastava, Harshit Agrawal:
Eye to I: Males Recognize Own Eye Movements, Females Inhibit Recognition. CogSci 2015 - [c15]Nisheeth Srivastava:
The spiral of anxiety: a cognitive account. CogSci 2015 - [c14]Nisheeth Srivastava, Ed Vul:
Attention dynamics in multiple object tracking. CogSci 2015 - [c13]Nisheeth Srivastava, Ed Vul:
Choosing fast and slow: explaining differences between hedonic and utilitarian choices. CogSci 2015 - 2014
- [c12]Nisheeth Srivastava, Paul R. Schrater:
Classical conditioning via inference over observable situation contexts. CogSci 2014 - [c11]Nisheeth Srivastava, Paul R. Schrater:
Frugal preference formation. CogSci 2014 - [c10]Nisheeth Srivastava, Ed Vul, Paul R. Schrater:
Magnitude-sensitive preference formation. NIPS 2014: 1080-1088 - 2013
- [c9]Komal Kapoor, Nisheeth Srivastava, Jaideep Srivastava, Paul R. Schrater:
Measuring spontaneous devaluations in user preferences. KDD 2013: 1061-1069 - 2012
- [j1]Amogh Mahapatra, Nisheeth Srivastava, Jaideep Srivastava
:
Contextual Anomaly Detection in Text Data. Algorithms 5(4): 469-489 (2012) - [c8]Prasanna Kumar Desikan, Nisheeth Srivastava, Tamara Winden, Tammie Lindquist, Heather Britt, Jaideep Srivastava
:
Early Prediction of Potentially Preventable Events in Ambulatory Care Sensitive Admissions from Clinical Data. HISB 2012: 124 - [c7]Komal Kapoor, Christopher Amato, Nisheeth Srivastava, Paul R. Schrater:
Using POMDPs to Control an Accuracy-Processing Time Trade-Off in Video Surveillance. IAAI 2012: 2293-2298 - [c6]Nisheeth Srivastava, Paul R. Schrater:
Rational inference of relative preferences. NIPS 2012: 2312-2320 - [c5]Amogh Mahapatra, Nisheeth Srivastava, Jaideep Srivastava
:
Characterizing the Internet's Sense of Humor. SocialCom/PASSAT 2012: 579-584 - 2011
- [c4]Nisheeth Srivastava, Paul R. Schrater:
A value-relativistic decision theory predicts known biases in human preferences. CogSci 2011 - [c3]Nisheeth Srivastava, Komal Kapoor, Paul R. Schrater:
A cognitive basis for theories of intrinsic motivation. ICDL-EPIROB 2011: 1-6 - [c2]Nisheeth Srivastava, Paul R. Schrater:
Cognitive Efficiency as a Causal Mechanism for Social Preferences. SocialCom/PASSAT 2011: 647-650
2000 – 2009
- 2009
- [c1]Aleksandar Lazarevic, Nisheeth Srivastava, Ashutosh Tiwari, Josh Isom, Nikunj C. Oza, Jaideep Srivastava
:
Theoretically Optimal Distributed Anomaly Detection. ICDM Workshops 2009: 515-520 - [i1]Nisheeth Srivastava:
Evolvability need not imply learnability. CoRR abs/0904.0648 (2009)
Coauthor Index
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