Ronny Luss

1.6k total citations
26 papers, 494 citations indexed

About

Ronny Luss is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Ronny Luss has authored 26 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Computational Mechanics. Recurrent topics in Ronny Luss's work include Explainable Artificial Intelligence (XAI) (9 papers), Sparse and Compressive Sensing Techniques (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Ronny Luss is often cited by papers focused on Explainable Artificial Intelligence (XAI) (9 papers), Sparse and Compressive Sensing Techniques (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Ronny Luss collaborates with scholars based in United States, Israel and United Kingdom. Ronny Luss's co-authors include Alexandre d’Aspremont, Marc Teboulle, Saharon Rosset, Moni Shahar, Amit Dhurandhar, Yunfeng Zhang, Karthikeyan Shanmugam, Q. Vera Liao, Finale Doshi‐Velez and Moninder Singh and has published in prestigious journals such as Journal of Machine Learning Research, SIAM Review and IBM Journal of Research and Development.

In The Last Decade

Ronny Luss

25 papers receiving 465 citations

Peers

Countries citing papers authored by Ronny Luss

Since Specialization

Citations

This map shows the geographic impact of Ronny Luss'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 Ronny Luss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronny Luss more than expected).

Fields of papers citing papers by Ronny Luss

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronny Luss. 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 Ronny Luss. The network helps show where Ronny Luss may publish in the future.

Co-authorship network of co-authors of Ronny Luss

This figure shows the co-authorship network connecting the top 25 collaborators of Ronny Luss. A scholar is included among the top collaborators of Ronny Luss based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ronny Luss. Ronny Luss is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models 2024 ·Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, (unknown), Aurélie Lozano, Payel Das, (unknown)	1
2	Local Explanations for Reinforcement Learning 2023 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Ronny Luss, Amit Dhurandhar, Miao Liu	1
3	Let the CAT out of the bag: Contrastive Attributed explanations for Text 2022 ·(unknown), Amar Prakash Azad, Ronny Luss, Amit Dhurandhar	2
4	AI Explainability 360: Impact and Design 2022 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Vijay Arya, Rachel Bellamy, Pin‐Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John R. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang	9
5	AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models 2020 ·Journal of Machine Learning Research ·Vijay Arya, Rachel Bellamy, Pin‐Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang	37
6	AI Explainability 360 Toolkit 2020 ·Vijay Arya, Rachel Bellamy, Pin‐Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang	19
7	Enhancing Simple Models by Exploiting What They Already Know 2019 ·arXiv (Cornell University) ·Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss	1
8	Leveraging Simple Model Predictions for Enhancing its Performance 2019 ·Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss	0
9	Beyond Backprop: Alternating Minimization with co-Activation Memory. 2018 ·arXiv (Cornell University) ·Anna Choromanska, (unknown), Ronny Luss, Irina Rish, Brian Kingsbury, (unknown), Djallel Bouneffouf	4
10	Improving Simple Models with Confidence Profiles 2018 ·arXiv (Cornell University) ·Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen	9
11	Detecting and Counting Panicles in Sorghum Images 2018 ·Peder A. Olsen, Karthikeyan Natesan Ramamurthy, (unknown), Yuhao Chen, Addie Thompson, Ronny Luss, Mitch Tuinstra, Naoki Abe	7
12	Interpretable policies for dynamic product recommendations 2016 ·Uncertainty in Artificial Intelligence ·Marek Petrik, Ronny Luss	5
13	Social media and customer behavior analytics for personalized customer engagements 2014 ·IBM Journal of Research and Development ·(unknown), Markus Ettl, Prateek Jain, Ronny Luss, Marek Petrik, (unknown), Chitra Venkatramani	13
14	Orthogonal Matching Pursuit for Sparse Quantile Regression 2014 ·Aleksandr Y. Aravkin, Aurélie Lozano, Ronny Luss, (unknown)	7
15	Predicting abnormal returns from news using text classification 2012 ·Quantitative Finance ·Ronny Luss, Alexandre d’Aspremont	94
16	Efficient regularized isotonic regression with application to gene–gene interaction search 2012 ·The Annals of Applied Statistics ·Ronny Luss, Saharon Rosset, Moni Shahar	34
17	Isotonic Recursive Partitioning 2011 ·arXiv (Cornell University) ·Ronny Luss, Saharon Rosset, Moni Shahar	1
18	Decomposing Isotonic Regression for Efficiently Solving Large Problems 2010 ·Neural Information Processing Systems ·Ronny Luss, Saharon Rosset, Moni Shahar	10
19	Convex approximations to sparse PCA via Lagrangian duality 2010 ·Operations Research Letters ·Ronny Luss, Marc Teboulle	9
20	Support vector machine classification with indefinite kernels 2009 ·Mathematical Programming Computation ·Ronny Luss, Alexandre d’Aspremont	65

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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