Irina Rish

ORCID

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 112

Top Venues

CoRR

NeurIPS

ICASSP

Trans. Mach. Learn. Res.

Publications

Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky
μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. CoRR (2024)
Ayush Kaushal, Tejas Pandey, Tejas Vaidhya, Aaryan Bhagat, Irina Rish
Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models. CoRR (2024)
Rishika Bhagwatkar, Shravan Nayak, Reza Bayat, Alexis Roger, Daniel Z. Kaplan, Pouya Bashivan, Irina Rish
Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques. CoRR (2024)
Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
Amplifying pathological detection in EEG signaling pathways through cross-dataset transfer learning. Comput. Biol. Medicine 169 (2024)
Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR (2024)
Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish
Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR (2024)
Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Jocelyn Faubert, Irina Rish
Dance of the Neurons: Unraveling Sex from Brain Signals (short paper). ML4CMH@AAAI (2024)
Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake A. Richards, Irina Rish, Özgür Simsek
Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent. CoRR (2024)
Tommaso Tosato, Pascal Tikeng Notsawo Jr., Saskia Helbling, Irina Rish, Guillaume Dumas
Lost in Translation: The Algorithmic Gap Between LMs and the Brain. CoRR (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas
Effective Latent Differential Equation Models via Attention and Multiple Shooting. Trans. Mach. Learn. Res. 2024 (2024)
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR (2024)
Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series. Trans. Mach. Learn. Res. 2023 (2023)
Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky
Gradient Masked Averaging for Federated Learning. Trans. Mach. Learn. Res. 2023 (2023)
Djallel Bouneffouf, Mayank Agarwal, Irina Rish
Dialogue System with Missing Observation. ICASSP (2023)
Pascal Tikeng Notsawo Jr., Hattie Zhou, Mohammad Pezeshki, Irina Rish, Guillaume Dumas
Predicting Grokking Long Before it Happens: A look into the loss landscape of models which grok. CoRR (2023)
Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Timothée Lesort, Md Rifat Arefin, Jocelyn Faubert, Irina Rish
Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning. CoRR (2023)
Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth
Maximum State Entropy Exploration using Predecessor and Successor Representations. NeurIPS (2023)
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
Lag-Llama: Towards Foundation Models for Time Series Forecasting. CoRR (2023)
Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs (2023)
Alexis Roger, Esma Aïmeur, Irina Rish
Towards ethical multimodal systems. CoRR (2023)
German Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Irina Rish, Pablo Polosecki, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas
GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models. CoRR (2023)
Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger
Broken Neural Scaling Laws. ICLR (2023)
Ayush Kaushal, Tejas Vaidhya, Irina Rish
LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression. CoRR (2023)
Baihan Lin, Djallel Bouneffouf, Irina Rish
A Survey on Compositional Generalization in Applications. CoRR (2023)
Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz
AI Agents Learn to Trust. CogSci (2023)
Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth
Maximum State Entropy Exploration using Predecessor and Successor Representations. CoRR (2023)
Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz
Towards Machines that Trust: AI Agents Learn to Trust in the Trust Game. CoRR (2023)
Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR (2023)
Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Eugene Belilovsky, Irina Rish
Gradient Masked Averaging for Federated Learning. CoRR (2022)
Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
Towards Continual Reinforcement Learning: A Review and Perspectives. J. Artif. Intell. Res. 75 (2022)
Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Guillaume Dumas, Irina Rish
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks. CoRR (2022)
Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, Irina Rish
APP: Anytime Progressive Pruning. CoRR (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Continual Learning with Foundation Models: An Empirical Study of Latent Replay. CoLLAs (2022)
Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger
Broken Neural Scaling Laws. CoRR (2022)
Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin, Pau Rodríguez, Laurent Charlin, Irina Rish
Scaling the Number of Tasks in Continual Learning. CoRR (2022)
Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish
Cognitive Models as Simulators: The Case of Moral Decision-Making. CoRR (2022)
Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
Towards Scaling Difference Target Propagation by Learning Backprop Targets. ICML (2022)
Alessio Mora, Irene Tenison, Paolo Bellavista, Irina Rish
Knowledge Distillation for Federated Learning: a Practical Guide. CoRR (2022)
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
Compositional Attention: Disentangling Search and Retrieval. ICLR (2022)
Mahta Ramezanian-Panahi, German Abrevaya, Jean-Christophe Gagnon-Audet, Vikram Voleti, Irina Rish, Guillaume Dumas
Generative Models of Brain Dynamics. Frontiers Artif. Intell. 5 (2022)
Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish
Cognitive Models as Simulators: The Case of Moral Decision-Making. CogSci (2022)
Jean-Christophe Gagnon-Audet, Soroosh Shahtalebi, Frank Rudzicz, Irina Rish
A Remedy For Distributional Shifts Through Expected Domain Translation. ICASSP (2022)
Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio
Towards Scaling Difference Target Propagation by Learning Backprop Targets. CoRR (2022)
Oleksiy Ostapenko, Timothée Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
Foundational Models for Continual Learning: An Empirical Study of Latent Replay. CoRR (2022)
Adam Ibrahim, Charles Guille-Escuret, Ioannis Mitliagkas, Irina Rish, David Krueger, Pouya Bashivan
Towards Out-of-Distribution Adversarial Robustness. CoRR (2022)
Jean-Charles Layoun, Alexis Roger, Irina Rish
Aligning MAGMA by Few-Shot Learning and Finetuning. CoRR (2022)
Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
Continual Learning In Environments With Polynomial Mixing Times. NeurIPS (2022)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CVPR (2022)
Gabriele Prato, Simon Guiroy, Ethan Caballero, Irina Rish, Sarath Chandar
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers. CoRR (2021)
Timothée Lesort, Massimo Caccia, Irina Rish
Understanding Continual Learning Settings with Data Distribution Drift Analysis. CoRR (2021)
Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
Continual Learning In Environments With Polynomial Mixing Times. CoRR (2021)
Timothée Lesort, Thomas George, Irina Rish
Continual Learning in Deep Networks: an Analysis of the Last Layer. CoRR (2021)
Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake A. Richards, Irina Rish
Adversarial Feature Desensitization. NeurIPS (2021)
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 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
Predicting Infectiousness for Proactive Contact Tracing. ICLR (2021)
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Irina Rish, Yasaman Khazaeni
Toward Optimal Solution for the Context-Attentive Bandit Problem. IJCAI (2021)
German 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
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33 (8) (2021)
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
Double-Linear Thompson Sampling for Context-Attentive Bandits. ICASSP (2021)
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
Compositional Attention: Disentangling Search and Retrieval. CoRR (2021)
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish
Toward Skills Dialog Orchestration with Online Learning. ICASSP (2021)
Sreya Francis, Irene Tenison, Irina Rish
Towards Causal Federated Learning For Enhanced Robustness and Privacy. CoRR (2021)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CoRR (2021)
Soroosh Shahtalebi, Jean-Christophe Gagnon-Audet, Touraj Laleh, Mojtaba Faramarzi, Kartik Ahuja, Irina Rish
SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization. CoRR (2021)
Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. NeurIPS (2021)
Nadhir Hassen, Irina Rish
Approximate Bayesian Optimisation for Neural Networks. CoRR (2021)
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
Sequoia: A Software Framework to Unify Continual Learning Research. CoRR (2021)
Irene Tenison, Sreya Francis, Irina Rish
Gradient Masked Federated Optimization. CoRR (2021)
Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR (2021)
Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR (2020)
Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS (2020)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI (2020)
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry. AAMAS (2020)
Pouya Bashivan, Blake A. Richards, Irina Rish
Adversarial Feature Desensitization. CoRR (2020)
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. HBAI@IJCAI (2020)
Victor Schmidt, Makesh Narsimhan Sreedhar, Mostafa ElAraby, Irina Rish
Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation. CoRR (2020)
Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal
Survey on Applications of Multi-Armed and Contextual Bandits. CEC (2020)
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 Buckeridge, Gaétan Marceau Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
Predicting Infectiousness for Proactive Contact Tracing. CoRR (2020)
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. CoRR (2020)
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 Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Joseph Pal, Joanna Merckx, Eilif B. Müller, Yoshua Bengio
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. CoRR (2020)
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
COVI White Paper. CoRR (2020)
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish
Double-Linear Thompson Sampling for Context-Attentive Bandits. CoRR (2020)
Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
Towards Continual Reinforcement Learning: A Review and Perspectives. CoRR (2020)
Jolie McDonnell, William Hord, Jenna M. Reinen, Pablo Polosecki, Irina Rish, Guillermo A. Cecchi
Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging (2019)
Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. ICML (2019)
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao
Kernelized Hashcode Representations for Relation Extraction. AAAI (2019)
Pouya Bashivan, Martin Schrimpf, Robert Ajemian, Irina Rish, Matthew Riemer, Yuhai Tu
Continual Learning with Self-Organizing Maps. CoRR (2019)
Djallel Bouneffouf, Irina Rish
A Survey on Practical Applications of Multi-Armed and Contextual Bandits. CoRR (2019)
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. ICLR (Poster) (2019)
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish
Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders. CoRR (2019)
Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan
Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI (2018)
Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Irina Rish
Contextual Bandit with Adaptive Feature Extraction. ICDM Workshops (2018)
German Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR (2018)
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Irina Rish
Adaptive Representation Selection in Contextual Bandit with Unlabeled History. CoRR (2018)
Anna Choromanska, Sadhana Kumaravel, Ronny Luss, Irina Rish, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf
Beyond Backprop: Alternating Minimization with co-Activation Memory. CoRR (2018)
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR (2018)
Guillermo A. Cecchi, Viatcheslav Gurev, Steve Heisig, Raquel Norel, Irina Rish, Samantha R. Schrecke
Computing the structure of language for neuropsychiatric evaluation. IBM J. Res. Dev. 61 (2/3) (2017)
Pablo Polosecki, Eduardo Castro, Andrew Wood, John H. Warner, Irina Rish, Guillermo A. Cecchi
Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease. IBM J. Res. Dev. 61 (2/3) (2017)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie C. Lozano
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. IJCAI (2017)
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi
Bandit Models of Human Behavior: Reward Processing in Mental Disorders. CoRR (2017)
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud
Context Attentive Bandits: Contextual Bandit with Restricted Context. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Irina Rish