Irina Rish - RankMe

208 papers A* 35A 10B 6Misc 7Journal 115Unranked 33

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent. CoRR Hiroki Naganuma, Shagun Gupta, Youssef Briki, Ioannis Mitliagkas, Irina Rish, Parameswaran Raman, Hao-Jun Michael Shi
2026	J	`jnl`	On the Adversarial Robustness of Discrete Image Tokenizers. CoRR Rishika Bhagwatkar, Irina Rish, Nicolas Flammarion, Francesco Croce
2026	A*	`conf`	Persistent Instability in LLM's Personality Measurements: Effects of Scale, Reasoning, and Conversation History. AAAI Tommaso Tosato, Saskia Helbling, Yorguin José Mantilla Ramos, Mahmood Hegazy, Alberto Tosato, David John Lemay, Irina Rish, Guillaume Dumas
2025	J	`jnl`	A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategy. CoRR Maxime Heuillet, Rishika Bhagwatkar, Jonas Ngnawé, Yann Pequignot, Alexandre Larouche, Christian Gagné, Irina Rish, Ola Ahmad, Audrey Durand
2025	A*	`conf`	AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. ICML Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham R. Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng
2025	J	`jnl`	Beyond Cosine Decay: On the effectiveness of Infinite Learning Rate Schedule for Continual Pre-training. CoRR Vaibhav Singh, Paul Janson, Paria Mehrbod, Adam Ibrahim, Irina Rish, Eugene Belilovsky, Benjamin Thérien
2025	J	`jnl`	Beyond Naïve Prompting: Strategies for Improved Zero-shot Context-aided Forecasting with LLMs. CoRR Arjun Ashok, Andrew Robert Williams, Vincent Zhihao Zheng, Irina Rish, Nicolas Chapados, Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin
2025	A*	`conf`	CAVE : Detecting and Explaining Commonsense Anomalies in Visual Environments. EMNLP Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou, Beatriz Borges, Irina Rish, Antoine Bosselut
2025	J	`jnl`	CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments. CoRR Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou, Beatriz Borges, Irina Rish, Antoine Bosselut
2025	A*	`conf`	Context is Key: A Benchmark for Forecasting with Essential Textual Information. ICML Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
2025	J	`jnl`	Continual Pre-training of MoEs: How robust is your router? CoRR Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish
2025	J	`jnl`	Continual Pre-training of MoEs: How robust is your router? Trans. Mach. Learn. Res. Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish
2025	A*	`conf`	Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. ICLR Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish
2025	J	`jnl`	GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities. CoRR Diganta Misra, Nizar Islah, Victor May, Brice Rauby, Zihan Wang, Justine Gehring, Antonio Orvieto, Muawiz Chaudhary, Eilif B. Muller, Irina Rish, Samira Ebrahimi Kahou, Massimo Caccia
2025	A*	`conf`	Handling Delay in Real-Time Reinforcement Learning. ICLR Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
2025	J	`jnl`	Handling Delay in Real-Time Reinforcement Learning. CoRR Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
2025	J	`jnl`	Image Tiling for High-Resolution Reasoning: Balancing Local Detail with Global Context. CoRR Anatole Jacquin de Margerie, Alexis Roger, Irina Rish
2025	J	`jnl`	Indirect Prompt Injections: Are Firewalls All You Need, or Stronger Benchmarks? CoRR Rishika Bhagwatkar, Kevin Kasa, Abhay Puri, Gabriel Huang, Irina Rish, Graham W. Taylor, Krishnamurthy Dj Dvijotham, Alexandre Lacoste
2025	J	`jnl`	Influence Functions for Efficient Data Selection in Reasoning. CoRR Prateek Humane, Paolo Cudrano, Daniel Z. Kaplan, Matteo Matteucci, Supriyo Chakraborty, Irina Rish
2025	J	`jnl`	Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. Trans. Mach. Learn. Res. Simon Dufort-Labbé, Pierluca D'Oro, Evgenii Nikishin, Irina Rish, Pierre-Luc Bacon, Razvan Pascanu, Aristide Baratin
2025	J	`jnl`	MuLoCo: Muon is a practical inner optimizer for DiLoCo. CoRR Benjamin Thérien, Xiaolong Huang, Irina Rish, Eugene Belilovsky
2025	A*	`conf`	Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. ICLR Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury
2025	J	`jnl`	Persistent Instability in LLM's Personality Measurements: Effects of Scale, Reasoning, and Conversation History. CoRR Tommaso Tosato, Saskia Helbling, Yorguin José Mantilla Ramos, Mahmood Hegazy, Alberto Tosato, David John Lemay, Irina Rish, Guillaume Dumas
2025	J	`jnl`	Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting. CoRR Roland Riachi, Kashif Rasul, Arjun Ashok, Prateek Humane, Alexis Roger, Andrew Robert Williams, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models. CoRR Istabrak Abbes, Gopeshh Subbaraj, Matthew Riemer, Nizar Islah, Benjamin Thérien, Tsuguchika Tabaru, Hiroaki Kingetsu, Sarath Chandar, Irina Rish
2025	J	`jnl`	Robin: a Suite of Multi-Scale Vision-Language Models and the CHIRP Evaluation Benchmark. CoRR Alexis Roger, Prateek Humane, Daniel Z. Kaplan, Kshitij Gupta, Qi Sun, George Adamopoulos, Jonathan Siu Chi Lim, Quentin Anthony, Edwin Fennell, Irina Rish
2025	—	`conf`	Scaling Laws and Efficient Inference for Ternary Language Models. ACL (1) Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish
2025	A*	`conf`	Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. ICLR Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal
2025	J	`jnl`	Small Vocabularies, Big Gains: Pretraining and Tokenization in Time Series Models. CoRR Alexis Roger, Gwen Legate, Kashif Rasul, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Spectra 1.1: Scaling Laws and Efficient Inference for Ternary Language Models. CoRR Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish
2025	A*	`conf`	Surprising Effectiveness of pretraining Ternary Language Model at Scale. ICLR Ayush Kaushal, Tejas Vaidhya, Arnab Kumar Mondal, Tejas Pandey, Aaryan Bhagat, Irina Rish
2025	—	`conf`	Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning. ACL (1) Andrei Mircea, Supriyo Chakraborty, Nima Chitsazan, Irina Rish, Ekaterina Lobacheva
2025	J	`jnl`	Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning. CoRR Andrei Mircea, Supriyo Chakraborty, Nima Chitsazan, Irina Rish, Ekaterina Lobacheva
2025	J	`jnl`	Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients. CoRR Gwen Legate, Irina Rish, Eugene Belilovsky
2024	J	`jnl`	Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. Comput. Biol. Medicine Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
2024	J	`jnl`	Context is Key: A Benchmark for Forecasting with Essential Textual Information. CoRR Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
2024	—	`conf`	Dance of the Neurons: Unraveling Sex from Brain Signals (short paper). ML4CMH@AAAI Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Jocelyn Faubert, Irina Rish
2024	B	`conf`	Decision-Making Paradoxes in Humans vs Machines: The case of the Allais and Ellsberg Paradoxes. CogSci Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz
2024	J	`jnl`	Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish
2024	J	`jnl`	Effective Latent Differential Equation Models via Attention and Multiple Shooting. Trans. Mach. Learn. Res. Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas
2024	J	`jnl`	Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. CoRR Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish
2024	J	`jnl`	GitChameleon: Unmasking the Version-Switching Capabilities of Code Generation Models. CoRR Nizar Islah, Justine Gehring, Diganta Misra, Eilif B. Müller, Irina Rish, Terry Yue Zhuo, Massimo Caccia
2024	—	`conf`	Improving Adversarial Robustness in Vision-Language Models with Architecture and Prompt Design. EMNLP (Findings) Rishika Bhagwatkar, Shravan Nayak, Pouya Bashivan, Irina Rish
2024	J	`jnl`	Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent. CoRR Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake A. Richards, Irina Rish, Özgür Simsek
2024	A*	`conf`	Knowledge Distillation in Federated Learning: A Practical Guide. IJCAI Alessio Mora, Irene Tenison, Paolo Bellavista, Irina Rish
2024	J	`jnl`	Lost in Translation: The Algorithmic Gap Between LMs and the Brain. CoRR Tommaso Tosato, Pascal Tikeng Notsawo Jr., Saskia Helbling, Irina Rish, Guillaume Dumas
2024	J	`jnl`	Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. CoRR Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury
2024	A*	`conf`	RedPajama: an Open Dataset for Training Large Language Models. NeurIPS Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	RedPajama: an Open Dataset for Training Large Language Models. CoRR Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. CoRR Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal
2024	J	`jnl`	Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
2024	J	`jnl`	Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
2024	J	`jnl`	Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models. CoRR Ayush Kaushal, Tejas Pandey, Tejas Vaidhya, Aaryan Bhagat, Irina Rish
2024	J	`jnl`	Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques. CoRR Rishika Bhagwatkar, Shravan Nayak, Reza Bayat, Alexis Roger, Daniel Z. Kaplan, Pouya Bashivan, Irina Rish
2024	A*	`conf`	Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2024	J	`jnl`	Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
2024	A*	`conf`	Using Unity to Help Solve Reinforcement Learning. NeurIPS Connor Brennan, Andrew Williams, Omar G. Younis, Vedant Vyas, Daria Yasafova, Irina Rish
2024	J	`jnl`	VFA: Vision Frequency Analysis of Foundation Models and Human. CoRR Mohammad-Javad Darvishi Bayazi, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
2024	J	`jnl`	μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. CoRR Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky
2023	J	`jnl`	A Survey on Compositional Generalization in Applications. CoRR Baihan Lin, Djallel Bouneffouf, Irina Rish
2023	B	`conf`	AI Agents Learn to Trust. CogSci Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz
2023	J	`jnl`	Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning. CoRR Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
2023	A*	`conf`	Broken Neural Scaling Laws. ICLR Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger
2023	—	`conf`	Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
2023	J	`jnl`	Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
2023	Misc	`conf`	Dialogue System with Missing Observation. ICASSP Djallel Bouneffouf, Mayank Agarwal, Irina Rish
2023	J	`jnl`	GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models. CoRR Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Irina Rish, Pablo Polosecki, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas
2023	J	`jnl`	Gradient Masked Averaging for Federated Learning. Trans. Mach. Learn. Res. Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky
2023	J	`jnl`	LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression. CoRR Ayush Kaushal, Tejas Vaidhya, Irina Rish
2023	J	`jnl`	Lag-Llama: Towards Foundation Models for Time Series Forecasting. CoRR Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Marin Bilos, Hena Ghonia, Nadhir Vincent Hassen, Anderson Schneider, Sahil Garg, Alexandre Drouin, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish
2023	A*	`conf`	Maximum State Entropy Exploration using Predecessor and Successor Representations. NeurIPS Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth
2023	J	`jnl`	Maximum State Entropy Exploration using Predecessor and Successor Representations. CoRR Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth
2023	J	`jnl`	Predicting Grokking Long Before it Happens: A look into the loss landscape of models which grok. CoRR Pascal Tikeng Notsawo Jr., Hattie Zhou, Mohammad Pezeshki, Irina Rish, Guillaume Dumas
2023	J	`jnl`	Towards Machines that Trust: AI Agents Learn to Trust in the Trust Game. CoRR Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz
2023	J	`jnl`	Towards ethical multimodal systems. CoRR Alexis Roger, Esma Aïmeur, Irina Rish
2023	J	`jnl`	WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series. Trans. Mach. Learn. Res. Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish
2022	Misc	`conf`	A Remedy For Distributional Shifts Through Expected Domain Translation. ICASSP Jean-Christophe Gagnon-Audet, Soroosh Shahtalebi, Frank Rudzicz, Irina Rish
2022	J	`jnl`	APP: Anytime Progressive Pruning. CoRR Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, Irina Rish
2022	J	`jnl`	Aligning MAGMA by Few-Shot Learning and Finetuning. CoRR Jean-Charles Layoun, Alexis Roger, Irina Rish
2022	J	`jnl`	Broken Neural Scaling Laws. CoRR Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger
2022	B	`conf`	Cognitive Models as Simulators: The Case of Moral Decision-Making. CogSci Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish
2022	J	`jnl`	Cognitive Models as Simulators: The Case of Moral Decision-Making. CoRR Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish
2022	A*	`conf`	Compositional Attention: Disentangling Search and Retrieval. ICLR Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
2022	A*	`conf`	Continual Learning In Environments With Polynomial Mixing Times. NeurIPS Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
2022	—	`conf`	Continual Learning with Foundation Models: An Empirical Study of Latent Replay. CoLLAs Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
2022	J	`jnl`	Foundational Models for Continual Learning: An Empirical Study of Latent Replay. CoRR Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
2022	J	`jnl`	Generative Models of Brain Dynamics. Frontiers Artif. Intell. Mahta Ramezanian-Panahi, Germán Abrevaya, Jean-Christophe Gagnon-Audet, Vikram Voleti, Irina Rish, Guillaume Dumas
2022	J	`jnl`	Gradient Masked Averaging for Federated Learning. CoRR Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Eugene Belilovsky, Irina Rish
2022	J	`jnl`	Knowledge Distillation for Federated Learning: a Practical Guide. CoRR Alessio Mora, Irene Tenison, Paolo Bellavista, Irina Rish
2022	A*	`conf`	Parametric Scattering Networks. CVPR Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
2022	J	`jnl`	Scaling the Number of Tasks in Continual Learning. CoRR Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish
2022	J	`jnl`	Towards Continual Reinforcement Learning: A Review and Perspectives. J. Artif. Intell. Res. Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
2022	J	`jnl`	Towards Out-of-Distribution Adversarial Robustness. CoRR Adam Ibrahim, Charles Guille-Escuret, Ioannis Mitliagkas, Irina Rish, David Krueger, Pouya Bashivan
2022	A*	`conf`	Towards Scaling Difference Target Propagation by Learning Backprop Targets. ICML Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
2022	J	`jnl`	Towards Scaling Difference Target Propagation by Learning Backprop Targets. CoRR Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
2022	J	`jnl`	WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks. CoRR Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Guillaume Dumas, Irina Rish
2021	A*	`conf`	Adversarial Feature Desensitization. NeurIPS Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake A. Richards, Irina Rish
2021	J	`jnl`	Approximate Bayesian Optimisation for Neural Networks. CoRR Nadhir Hassen, Irina Rish
2021	J	`jnl`	Compositional Attention: Disentangling Search and Retrieval. CoRR Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
2021	J	`jnl`	Continual Learning In Environments With Polynomial Mixing Times. CoRR Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
2021	J	`jnl`	Continual Learning in Deep Networks: an Analysis of the Last Layer. CoRR Timothée Lesort, Thomas George, Irina Rish
2021	Misc	`conf`	Double-Linear Thompson Sampling for Context-Attentive Bandits. ICASSP Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
2021	J	`jnl`	Gradient Masked Federated Optimization. CoRR Irene Tenison, Sreya Francis, Irina Rish
2021	A*	`conf`	Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. NeurIPS Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish
2021	J	`jnl`	Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish
2021	J	`jnl`	Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish
2021	J	`jnl`	Parametric Scattering Networks. CoRR Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
2021	A*	`conf`	Predicting Infectiousness for Proactive Contact Tracing. ICLR Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
2021	J	`jnl`	SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization. CoRR Soroosh Shahtalebi, Jean-Christophe Gagnon-Audet, Touraj Laleh, Mojtaba Faramarzi, Kartik Ahuja, Irina Rish
2021	J	`jnl`	Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers. CoRR Gabriele Prato, Simon Guiroy, Ethan Caballero, Irina Rish, Sarath Chandar
2021	J	`jnl`	Sequoia: A Software Framework to Unify Continual Learning Research. CoRR Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia
2021	A*	`conf`	Toward Optimal Solution for the Context-Attentive Bandit Problem. IJCAI Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Irina Rish, Yasaman Khazaeni
2021	Misc	`conf`	Toward Skills Dialog Orchestration with Online Learning. ICASSP Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish
2021	J	`jnl`	Towards Causal Federated Learning For Enhanced Robustness and Privacy. CoRR Sreya Francis, Irene Tenison, Irina Rish
2021	J	`jnl`	Understanding Continual Learning Settings with Data Distribution Drift Analysis. CoRR Timothée Lesort, Massimo Caccia, Irina Rish
2020	A	`conf`	A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry. AAMAS Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
2020	J	`jnl`	Adversarial Feature Desensitization. CoRR Pouya Bashivan, Blake A. Richards, Irina Rish
2020	J	`jnl`	COVI White Paper. CoRR Hannah Alsdurf, Yoshua Bengio, Tristan Deleu, Prateek Gupta, Daphne Ippolito, Richard Janda, Max Jarvie, Tyler Kolody, Sekoul Krastev, Tegan Maharaj, Robert Obryk, Dan Pilat, Valerie Pisano, Benjamin Prud'homme, Meng Qu, Nasim Rahaman, Irina Rish, Jean-Franois Rousseau, Abhinav Sharma, Brooke Struck, Jian Tang, Martin Weiss, Yun William Yu
2020	J	`jnl`	COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. CoRR Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St-Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David L. Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Joseph Pal, Joanna Merckx, Eilif B. Müller, Yoshua Bengio
2020	J	`jnl`	Double-Linear Thompson Sampling for Context-Attentive Bandits. CoRR Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
2020	A*	`conf`	Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan
2020	—	`conf`	Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. HBAI@IJCAI Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
2020	A*	`conf`	Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
2020	J	`jnl`	Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
2020	J	`jnl`	Predicting Infectiousness for Proactive Contact Tracing. CoRR Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B. Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
2020	B	`conf`	Survey on Applications of Multi-Armed and Contextual Bandits. CEC Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal
2020	J	`jnl`	Towards Continual Reinforcement Learning: A Review and Perspectives. CoRR Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
2020	J	`jnl`	Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation. CoRR Victor Schmidt, Makesh Narsimhan Sreedhar, Mostafa ElAraby, Irina Rish
2020	J	`jnl`	Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. CoRR Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
2019	J	`jnl`	A Survey on Practical Applications of Multi-Armed and Contextual Bandits. CoRR Djallel Bouneffouf, Irina Rish
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`	Continual Learning with Self-Organizing Maps. CoRR Pouya Bashivan, Martin Schrimpf, Robert Ajemian, Irina Rish, Matthew Riemer, Yuhai Tu
2019	A*	`conf`	Kernelized Hashcode Representations for Relation Extraction. AAAI Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao
2019	—	`conf`	Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. ICLR (Poster) Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2019	—	`conf`	Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features. Biomedical Applications in Molecular, Structural, and Functional Imaging Jolie McDonnell, William Hord, Jenna M. Reinen, Pablo Polosecki, Irina Rish, Guillermo A. Cecchi
2019	J	`jnl`	Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders. CoRR Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
2018	J	`jnl`	Adaptive Representation Selection in Contextual Bandit with Unlabeled History. CoRR Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Irina Rish
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	—	`conf`	Contextual Bandit with Adaptive Feature Extraction. ICDM Workshops Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Irina Rish
2018	—	`conf`	Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan
2018	J	`jnl`	Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR Germán Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson
2018	J	`jnl`	Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2017	—	`conf`	Bandit Models of Human Behavior: Reward Processing in Mental Disorders. AGI Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi
2017	J	`jnl`	Bandit Models of Human Behavior: Reward Processing in Mental Disorders. CoRR Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi
2017	J	`jnl`	Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease. IBM J. Res. Dev. Pablo Polosecki, Eduardo Castro, Andrew Wood, John H. Warner, Irina Rish, Guillermo A. Cecchi
2017	J	`jnl`	Computing the structure of language for neuropsychiatric evaluation. IBM J. Res. Dev. Guillermo A. Cecchi, Viatcheslav Gurev, Steve Heisig, Raquel Norel, Irina Rish, Samantha R. Schrecke
2017	A*	`conf`	Context Attentive Bandits: Contextual Bandit with Restricted Context. IJCAI Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud
2017	J	`jnl`	Context Attentive Bandits: Contextual Bandit with Restricted Context. CoRR Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud
2017	J	`jnl`	Efficient Representation for Natural Language Processing via Kernelized Hashcodes. CoRR Sahil Garg, Aram Galstyan, Irina Rish, Guillermo A. Cecchi, Shuyang Gao
2017	J	`jnl`	Holographic brain: Distributed versus local activation patterns in fMRI. IBM J. Res. Dev. Irina Rish, Guillermo A. Cecchi
2017	J	`jnl`	Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks. CoRR Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner
2017	—	`conf`	Learning discriminative functional network features of schizophrenia. Biomedical Applications in Molecular, Structural, and Functional Imaging Mina Gheiratmand, Irina Rish, Guillermo A. Cecchi, Matthew R. G. Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar M. Dursun
2017	—	`conf`	Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. ICLR (Workshop) Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano
2017	A*	`conf`	Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. IJCAI Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano
2017	J	`jnl`	Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. CoRR Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano
2016	—	`conf`	Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach. Biomedical Applications in Molecular, Structural, and Functional Imaging Irina Rish, Pouya Bashivan, Guillermo A. Cecchi, Rita Z. Goldstein
2016	A*	`conf`	Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks. ICLR (Poster) Pouya Bashivan, Irina Rish, Mohammed Yeasin, Noel Codella
2016	J	`jnl`	MINT: Mutual Information Based Transductive Feature Selection for Genetic Trait Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. Dan He, Irina Rish, David Haws, Laxmi Parida
2016	—	`ed.`	Machine Learning and Interpretation in Neuroimaging - 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers MLINI@NIPS Irina Rish, Georg Langs, Leila Wehbe, Guillermo A. Cecchi, Kai-min Kevin Chang, Brian Murphy
2016	J	`jnl`	Mental State Recognition via Wearable EEG. CoRR Pouya Bashivan, Irina Rish, Steve Heisig
2014	A	`conf`	Transductive HSIC Lasso. SDM Dan He, Irina Rish, Laxmi Parida
2013	J	`jnl`	A Scheme for Approximating Probabilistic Inference CoRR Rina Dechter, Irina Rish
2013	J	`jnl`	Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding CoRR Irina Rish, Kalev Kask, Rina Dechter
2013	—	`conf`	Functional MRI Analysis with Sparse Models. ECML/PKDD (3) Irina Rish
2013	J	`jnl`	MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction. CoRR Dan He, Irina Rish, David Haws, Simon Teyssedre, Zivan Karaman, Laxmi Parida
2012	J	`jnl`	Efficient Test Selection in Active Diagnosis via Entropy Approximation CoRR Alice X. Zheng, Irina Rish, Alina Beygelzimer
2012	—	`ed.`	Machine Learning and Interpretation in Neuroimaging - International Workshop, MLINI 2011, Held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised Selected and Invited Contributions MLINI Georg Langs, Irina Rish, Moritz Grosse-Wentrup, Brian Murphy
2012	J	`jnl`	Predictive Dynamics of Human Pain Perception. PLoS Comput. Biol. Guillermo A. Cecchi, Lejian Huang, Javeria Ali Hashmi, Marwan N. Baliki, María V. Centeno, Irina Rish, Apkar Vania Apkarian
2012	B	`conf`	Sparse regression analysis of task-relevant information distribution in the brain. Image Processing Irina Rish, Guillermo A. Cecchi, Kyle Heuton, Marwan N. Baliki, Apkar Vania Apkarian
2012	A	`conf`	Variable Selection for Gaussian Graphical Models. AISTATS Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo A. Cecchi
2010	—	`conf`	Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach. ECML/PKDD (3) Katya Scheinberg, Irina Rish
2010	Misc	`conf`	Sparse Markov net learning with priors on regularization parameters. ISAIM Katya Scheinberg, Irina Rish, Narges Bani Asadi
2010	—	`conf`	Sparse Regression Models of Pain Perception. Brain Informatics Irina Rish, Guillermo A. Cecchi, Marwan N. Baliki, Apkar Vania Apkarian
2009	—	`conf`	Discriminative Network Models of Schizophrenia. NIPS Guillermo A. Cecchi, Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillère-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline
2009	Misc	`conf`	Map approach to learning sparse Gaussian Markov networks. ICASSP Narges Bani Asadi, Irina Rish, Katya Scheinberg, Dimitri Kanevsky, Bhuvana Ramabhadran
2009	J	`jnl`	Prediction and interpretation of distributed neural activity with sparse models. NeuroImage Melissa K. Carroll, Guillermo A. Cecchi, Irina Rish, Rahul Garg, A. Ravishankar Rao
2009	—	`conf`	Sparse signal recovery with exponential-family noise. Allerton Irina Rish, Genady Grabarnik
2008	Misc	`conf`	Active Collaborative Prediction with Maximum Margin Matrix Factorization. ISAIM Irina Rish, Gerald Tesauro
2008	A*	`conf`	Closed-form supervised dimensionality reduction with generalized linear models. ICML Irina Rish, Genady Grabarnik, Guillermo A. Cecchi, Francisco Pereira, Geoffrey J. Gordon
2007	A	`conf`	Blind source separation approach to performance diagnosis and dependency discovery. Internet Measurement Conference Gaurav Chandalia, Irina Rish
2007	B	`conf`	Empirical Study of Topology Effects on Diagnosis in Computer Networks. MASS Natalia Odintsova, Irina Rish
2007	—	`conf`	Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. Integrated Network Management Irina Rish, Gerald Tesauro
2007	—	`conf`	Evaluation of Optimization Methods for Network Bottleneck Diagnosis. ICAC Alina Beygelzimer, Jeffrey O. Kephart, Irina Rish
2006	—	`conf`	Bayesian Learning of Markov Network Structure. ECML Aleks Jakulin, Irina Rish
2005	J	`jnl`	Adaptive diagnosis in distributed systems. IEEE Trans. Neural Networks Irina Rish, Mark Brodie, Sheng Ma, Natalia Odintsova, Alina Beygelzimer, Genady Grabarnik, Karina Hernandez
2005	A	`conf`	Efficient Test Selection in Active Diagnosis via Entropy Approximation. UAI Alice X. Zheng, Irina Rish, Alina Beygelzimer
2005	A	`conf`	Statictical Models for Unequally Spaced Time Series. SDM Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish
2005	—	`conf`	Test-based diagnosis: tree and matrix representations. Integrated Network Management Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish
2004	—	`conf`	Improving Network Robustness. ICAC Alina Beygelzimer, Geoffrey Grinstein, Ralph Linsker, Irina Rish
2004	—	`conf`	Real-time problem determination in distributed systems using active probing. NOMS (1) Irina Rish, Mark Brodie, Natalia Odintsova, Sheng Ma, Genady Grabarnik
2003	—	`conf`	A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes. ECML Ricardo Vilalta, Irina Rish
2003	A*	`conf`	Active Probing Strategies for Problem Diagnosis in Distributed Systems. IJCAI Mark Brodie, Irina Rish, Sheng Ma, Natalia Odintsova
2003	—	`conf`	Approximability of Probability Distributions. NIPS Alina Beygelzimer, Irina Rish
2003	A*	`conf`	Critical event prediction for proactive management in large-scale computer clusters. KDD Ramendra K. Sahoo, Adam J. Oliner, Irina Rish, Manish Gupta, José E. Moreira, Sheng Ma, Ricardo Vilalta, Anand Sivasubramaniam
2003	J	`jnl`	Mini-buckets: A general scheme for bounded inference. J. ACM Rina Dechter, Irina Rish
2002	—	`conf`	Accuracy vs. Efficiency Trade-offs in Probabilistic Diagnosis. AAAI/IAAI Irina Rish, Mark Brodie, Sheng Ma
2002	A*	`conf`	Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. KR Alina Beygelzimer, Irina Rish
2002	J	`jnl`	Intelligent probing: A cost-effective approach to fault diagnosis in computer networks. IBM Syst. J. Mark Brodie, Irina Rish, Sheng Ma
2001	—	`conf`	A Unified Framework for Evaluation Metrics in Classification Using Decision Trees. ECML Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish
2001	—	`conf`	Optimizing Probe Selection for Fault Localization. DSOM Mark Brodie, Irina Rish, Sheng Ma
2000	—	`conf`	Recognizing End-User Transactions in Performance Management. AAAI/IAAI Joseph L. Hellerstein, T. S. Jayram, Irina Rish
2000	J	`jnl`	Resolution versus Search: Two Strategies for SAT. J. Autom. Reason. Irina Rish, Rina Dechter
1998	A	`conf`	Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding. UAI Irina Rish, Kalev Kask, Rina Dechter
1997	A	`conf`	A Scheme for Approximating Probabilistic Inference. UAI Rina Dechter, Irina Rish
1997	A	`conf`	Statistical Analysis of Backtracking on Inconsistent CSPs. CP Irina Rish, Daniel Frost
1997	—	`conf`	Summarizing CSP Hardness with Continuous Probability Distributions. AAAI/IAAI Daniel Frost, Irina Rish, Lluís Vila
1996	A	`conf`	To Guess or to Think? Hybrid Algorithms for SAT (Extended Abstract). CP Irina Rish, Rina Dechter
1994	A*	`conf`	Directional Resolution: The Davis-Putnam Procedure, Revisited. KR Rina Dechter, Irina Rish