Harikrishna Narasimhan

1.7k citations
49 papers · 644 indexed · h-index 17

Harikrishna Narasimhan

47 papers receiving 619 citations

Peers

Harikrishna Narasimhan
Comparison fields: 5 of 100
  • Management Science and Operations Research 139
  • Artificial Intelligence 324
  • Safety Research 51
  • Computer Science Applications 32
  • Health Informatics 7
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Citations per year

Countries citing papers authored by Harikrishna Narasimhan

Since Specialization
Citations

This map shows the geographic impact of Harikrishna Narasimhan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Harikrishna Narasimhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harikrishna Narasimhan more than expected).

Fields of papers citing papers by Harikrishna Narasimhan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harikrishna Narasimhan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Harikrishna Narasimhan. The network helps show where Harikrishna Narasimhan may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Harikrishna Narasimhan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Harikrishna Narasimhan Line = papers co-authored together Harikrishna Narasimhan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 202318
3 20230
4
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
20202
5
On Making Stochastic Classifiers Deterministic
20191
6
Optimal Auctions through Deep Learning
201937
7
Optimizing Generalized Rate Metrics with Three Players
20194
8
Learning with Complex Loss Functions and Constraints.
201823
9 201815
10
A general statistical framework for designing strategy-proof assignment mechanisms
20163
11
Stochastic Optimization Techniques for Quantification Performance Measures
20164
12 201619
13
Bayes optimal feature selection for supervised learning with general performance measures
20151
14
Learnability of influence in networks
201524
15
Consistent Multiclass Algorithms for Complex Performance Measures
201511
16
On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures
201432
17
A Structural SVM Based Approach for Optimizing Partial AUC
201337
18
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
201333
19
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation
201316
20
Towards a Cooperative Defense Model Against Network Security Attacks.
20108

About Harikrishna Narasimhan

Harikrishna Narasimhan is a scholar working on Management Science and Operations Research, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 49 papers that have together received 644 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (12 papers), Imbalanced Data Classification Techniques (11 papers), Machine Learning and Data Classification (9 papers), Auction Theory and Applications (8 papers), Consumer Market Behavior and Pricing (5 papers), Fire effects on concrete materials (5 papers), Probabilistic and Robust Engineering Design (4 papers) and Advanced Bandit Algorithms Research (4 papers). The work is most often cited by research in Management Science and Operations Research (139 citations), Artificial Intelligence (324 citations) and Safety Research (51 citations). Harikrishna Narasimhan has collaborated with scholars based in United States, India and Denmark. Frequent co-authors include Shivani Agarwal, David C. Parkes, Zhe Feng, Maya R. Gupta, Andrew Cotter, Michael Yit Lin Chew, Purushottam Kar, Paul Dütting, Sanjay Chawla and Yaron Singer. Their work appears in journals such as Communications of the ACM, Construction and Building Materials and Journal of the ACM.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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