Luss, Ronny

17 publications

ICLR 2025 Shedding Light on Time Series Classification Using Interpretability Gated Networks Yunshi Wen, Tengfei Ma, Ronny Luss, Debarun Bhattacharjya, Achille Fokoue, Anak Agung Julius

IJCAI 2024 ComVas: Contextual Moral Values Alignment System Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

TMLR 2024 To Transfer or Not to Transfer: Suppressing Concepts from Source Representations Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris Sims, James Hendler, Amit Dhurandhar

TMLR 2024 When Stability Meets Sufficiency: Informative Explanations That Do Not Overwhelm Ronny Luss, Amit Dhurandhar

AAAI 2023 Local Explanations for Reinforcement Learning Ronny Luss, Amit Dhurandhar, Miao Liu

IJCAI 2023 Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models Debarun Bhattacharjya, Oktie Hassanzadeh, Ronny Luss, Keerthiram Murugesan

ICLR 2023 Weighted Clock Logic Point Process Ruixuan Yan, Yunshi Wen, Debarun Bhattacharjya, Ronny Luss, Tengfei Ma, Achille Fokoue, Anak Agung Julius

AAAI 2022 AI Explainability 360: Impact and Design 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

ICLR 2022 Auto-Transfer: Learning to Route Transferable Representations Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

MLOSS 2020 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models Vijay Arya, Rachel K. E. 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

ICML 2020 Enhancing Simple Models by Exploiting What They Already Know Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

ICML 2019 Beyond Backprop: Online Alternating Minimization with Auxiliary Variables Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf

NeurIPS 2018 Explanations Based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, Payel Das

NeurIPS 2018 Improving Simple Models with Confidence Profiles Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen

UAI 2016 Interpretable Policies for Dynamic Product Recommendations Marek Petrik, Ronny Luss

NeurIPS 2010 Decomposing Isotonic Regression for Efficiently Solving Large Problems Ronny Luss, Saharon Rosset, Moni Shahar

NeurIPS 2007 Support Vector Machine Classification with Indefinite Kernels Ronny Luss, Alexandre D'aspremont