Ronny Luss - RankMe

60 papers A* 14A 1B 2Misc 1Journal 34Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Contextual Value Alignment. ICASSP Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2025	J	`jnl`	ICX360: In-Context eXplainability 360 Toolkit. CoRR Dennis Wei, Ronny Luss, Xiaomeng Hu, Lucas Monteiro Paes, Pin-Yu Chen, Karthikeyan Natesan Ramamurthy, Erik Miehling, Inge Vejsbjerg, Hendrik Strobelt
2025	—	`conf`	Multi-Level Explanations for Generative Language Models. ACL (1) Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
2025	A*	`conf`	Shedding Light on Time Series Classification using Interpretability Gated Networks. ICLR Yunshi Wen, Tengfei Ma, Ronny Luss, Debarun Bhattacharjya, Achille Fokoue, Anak Agung Julius
2025	—	`conf`	Sparsity May Be All You Need: Sparse Random Parameter Adaptation. EMNLP (Findings) Jesus Rios, Pierre L. Dognin, Ronny Luss, Karthikeyan Natesan Ramamurthy
2025	J	`jnl`	Sparsity May Be All You Need: Sparse Random Parameter Adaptation. CoRR Jesus Rios, Pierre L. Dognin, Ronny Luss, Karthikeyan Ramamurthy
2024	J	`jnl`	CELL your Model: Contrastive Explanation Methods for Large Language Models. CoRR Ronny Luss, Erik Miehling, Amit Dhurandhar
2024	A*	`conf`	ComVas: Contextual Moral Values Alignment System. IJCAI Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024	J	`jnl`	Contextual Moral Value Alignment Through Context-Based Aggregation. CoRR Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024	J	`jnl`	Multi-Level Explanations for Generative Language Models. CoRR Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
2024	—	`conf`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. ACL (Findings) Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. CoRR Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	To Transfer or Not to Transfer: Suppressing Concepts from Source Representations. Trans. Mach. Learn. Res. Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris R. Sims, James A. Hendler, Amit Dhurandhar
2024	J	`jnl`	When Stability meets Sufficiency: Informative Explanations that do not Overwhelm. Trans. Mach. Learn. Res. Ronny Luss, Amit Dhurandhar
2023	A*	`conf`	Local Explanations for Reinforcement Learning. AAAI Ronny Luss, Amit Dhurandhar, Miao Liu
2023	A*	`conf`	Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models. IJCAI Debarun Bhattacharjya, Oktie Hassanzadeh, Ronny Luss, Keerthiram Murugesan
2023	—	`conf`	Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge. EMNLP (Findings) Shajith Ikbal, Udit Sharma, Hima Karanam, Sumit Neelam, Ronny Luss, Dheeraj Sreedhar, Pavan Kapanipathi, Naweed Khan, Kyle Erwin, Ndivhuwo Makondo, Ibrahim Abdelaziz, Achille Fokoue, Alexander Gray, Maxwell Crouse, Subhajit Chaudhury, Chitra Subramanian
2023	A*	`conf`	Weighted Clock Logic Point Process. ICLR Ruixuan Yan, Yunshi Wen, Debarun Bhattacharjya, Ronny Luss, Tengfei Ma, Achille Fokoue, Anak Agung Julius
2022	A*	`conf`	AI Explainability 360: Impact and Design. AAAI Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2022	A*	`conf`	Auto-Transfer: Learning to Route Transferable Representations. ICLR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	J	`jnl`	Auto-Transfer: Learning to Route Transferrable Representations. CoRR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	B	`conf`	Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. HCOMP Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
2022	J	`jnl`	Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. CoRR Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
2022	A*	`conf`	Let the CAT out of the bag: Contrastive Attributed explanations for Text. EMNLP Saneem A. Chemmengath, Amar Prakash Azad, Ronny Luss, Amit Dhurandhar
2022	J	`jnl`	Local Explanations for Reinforcement Learning. CoRR Ronny Luss, Amit Dhurandhar, Miao Liu
2021	—	`conf`	AI Explainability 360 Toolkit. COMAD/CODS Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021	J	`jnl`	AI Explainability 360: Impact and Design. CoRR Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021	J	`jnl`	Let the CAT out of the bag: Contrastive Attributed explanations for Text. CoRR Saneem A. Chemmengath, Amar Prakash Azad, Ronny Luss, Amit Dhurandhar
2021	A*	`conf`	Leveraging Latent Features for Local Explanations. KDD Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu
2021	J	`jnl`	Towards Better Model Understanding with Path-Sufficient Explanations. CoRR Ronny Luss, Amit Dhurandhar
2020	J	`jnl`	AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020	—	`conf`	AI explainability 360: hands-on tutorial. FAT* Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020	A*	`conf`	Enhancing Simple Models by Exploiting What They Already Know. ICML Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
2019	A*	`conf`	Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. ICML Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf
2019	J	`jnl`	Generating Contrastive Explanations with Monotonic Attribute Functions. CoRR Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu
2019	J	`jnl`	Leveraging Simple Model Predictions for Enhancing its Performance. CoRR Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
2019	J	`jnl`	One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. CoRR Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2018	J	`jnl`	Beyond Backprop: Alternating Minimization with co-Activation Memory. CoRR Anna Choromanska, Sadhana Kumaravel, Ronny Luss, Irina Rish, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf
2018	B	`conf`	Detecting and Counting Panicles in Sorghum Images. DSAA Peder A. Olsen, Karthikeyan Natesan Ramamurthy, Javier Ribera, Yuhao Chen, Addie M. Thompson, Ronny Luss, Mitch Tuinstra, Naoki Abe
2018	A*	`conf`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. NeurIPS Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	J	`jnl`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. CoRR Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	A*	`conf`	Improving Simple Models with Confidence Profiles. NeurIPS Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen
2018	J	`jnl`	Improving Simple Models with Confidence Profiles. CoRR Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen
2018	J	`jnl`	Stochastic Gradient Descent with Biased but Consistent Gradient Estimators. CoRR Jie Chen, Ronny Luss
2017	J	`jnl`	A Formal Framework to Characterize Interpretability of Procedures. CoRR Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam
2017	J	`jnl`	TIP: Typifying the Interpretability of Procedures. CoRR Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam
2016	A	`conf`	Interpretable Policies for Dynamic Product Recommendations. UAI Marek Petrik, Ronny Luss
2014	A*	`conf`	Orthogonal Matching Pursuit for Sparse Quantile Regression. ICDM Aleksandr Y. Aravkin, Aurélie C. Lozano, Ronny Luss, Prabhanjan Kambadur
2014	J	`jnl`	Social media and customer behavior analytics for personalized customer engagements. IBM J. Res. Dev. Stephen J. Buckley, Markus Ettl, Prateek Jain, Ronny Luss, Marek Petrik, Rajesh Kumar Ravi, Chitra Venkatramani
2014	J	`jnl`	Sparse Quantile Huber Regression for Efficient and Robust Estimation. CoRR Aleksandr Y. Aravkin, Anju Kambadur, Aurélie C. Lozano, Ronny Luss
2013	J	`jnl`	Conditional Gradient Algorithmsfor Rank-One Matrix Approximations with a Sparsity Constraint. SIAM Rev. Ronny Luss, Marc Teboulle
2011	J	`jnl`	Conditional Gradient Algorithms for Rank-One Matrix Approximations with a Sparsity Constraint CoRR Ronny Luss, Marc Teboulle
2011	J	`jnl`	Convex approximations to sparse PCA via Lagrangian duality. Oper. Res. Lett. Ronny Luss, Marc Teboulle
2011	J	`jnl`	Isotonic Recursive Partitioning CoRR Ronny Luss, Saharon Rosset, Moni Shahar
2010	—	`conf`	Decomposing Isotonic Regression for Efficiently Solving Large Problems. NIPS Ronny Luss, Saharon Rosset, Moni Shahar
2009	J	`jnl`	Support vector machine classification with indefinite kernels. Math. Program. Comput. Ronny Luss, Alexandre d'Aspremont
2008	J	`jnl`	A Cutting Plane Method for Multiple Kernel Learning CoRR Ronny Luss, Alexandre d'Aspremont
2008	J	`jnl`	Support Vector Machine Classification with Indefinite Kernels CoRR Ronny Luss, Alexandre d'Aspremont
2007	J	`jnl`	Clustering and Feature Selection using Sparse Principal Component Analysis CoRR Ronny Luss, Alexandre d'Aspremont
2007	—	`conf`	Support Vector Machine Classification with Indefinite Kernels. NIPS Ronny Luss, Alexandre d'Aspremont