| 2026 | AAAI | Multi-Armed Bandits Meet Large Language Models. | Djallel Bouneffouf, Raphal Fraud |
| 2026 | AAAI | The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships? | Djallel Bouneffouf, Matthew Riemer, Kush R. Varshney |
| 2026 | WWW | Can Large Language Models Govern Themselves? A Technical, Ethical, and Governance Perspective. | Djallel Bouneffouf |
| 2026 | WWW | Ethical Decision-Making under Moral Uncertainty. | Djallel Bouneffouf |
| 2026 | WWW | LLM and AI Agent: Golden Rule is All We Need. | Djallel Bouneffouf |
| 2026 | WWW | Bandits, LLMs, and Agentic Web. | Djallel Bouneffouf, Raphal Fraud |
| 2025 | ICASSP | Multi-Armed Bandit with Sparse and Noisy Feedback. | Djallel Bouneffouf, Raphal Fraud, Baihan Lin |
| 2025 | ICASSP | Contextual Value Alignment. | Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf |
| 2025 | ICML | Position: Theory of Mind Benchmarks are Broken for Large Language Models. | Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell |
| 2025 | IJCAI | LLMs in Court: Risks and Governance of LLMs in Judicial Decision-Making. | Djallel Bouneffouf, Sara Migliorini |
| 2025 | IUI | TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts (short paper). | Baihan Lin, Stefan Zecevic, Djallel Bouneffouf, Guillermo A. Cecchi |
| 2025 | NAACL | Evaluating the Prompt Steerability of Large Language Models. | Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu, Prasanna Sattigeri |
| 2024 | IJCAI | 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 |
| 2024 | KDD | A Tutorial on Multi-Armed Bandit Applications for Large Language Models. | Djallel Bouneffouf, Raphal Fraud |
| 2023 | ICASSP | Question Answering System with Sparse and Noisy Feedback. | Djallel Bouneffouf, Oznur Alkan, Raphal Fraud, Baihan Lin |
| 2023 | ICASSP | Dialogue System with Missing Observation. | Djallel Bouneffouf, Mayank Agarwal, Irina Rish |
| 2023 | IJCAI | SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning. | Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf |
| 2023 | IUI | Helping Therapists with NLP-Annotated Recommendation 17-24. | Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf |
| 2023 | WWW | Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics. | Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf |
| 2023 | WWW | Robust Stochastic Multi-Armed Bandits with Historical Data. | Sarah Boufelja Yacobi, Djallel Bouneffouf |
| 2022 | AAAI | Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization. | Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea |
| 2022 | IJCAI | Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. | Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu |
| 2022 | IJCNN | Linear Upper Confident Bound with Missing Reward: Online Learning with Less Data. | Djallel Bouneffouf, Sohini Upadhyay, Yasaman Khazaeni |
| 2022 | IJCNN | Predicting Human Decision Making with LSTM. | Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi |
| 2022 | PRICAI | Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior. | Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi |
| 2022 | UAI | Linearizing contextual bandits with latent state dynamics. | Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart |
| 2021 | ICASSP | Corrupted Contextual Bandits: Online Learning with Corrupted Context. | Djallel Bouneffouf |
| 2021 | ICASSP | Online Hyper-Parameter Tuning for the Contextual Bandit. | Djallel Bouneffouf, Emmanuelle Claeys |
| 2021 | ICASSP | Toward Skills Dialog Orchestration with Online Learning. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish |
| 2021 | ICASSP | Double-Linear Thompson Sampling for Context-Attentive Bandits. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish |
| 2021 | IJCAI | Toward Optimal Solution for the Context-Attentive Bandit Problem. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Irina Rish, Yasaman Khazaeni |
| 2020 | AAAI | An ADMM Based Framework for AutoML Pipeline Configuration. | Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray |
| 2020 | AIES | Data Augmentation for Discrimination Prevention and Bias Disambiguation. | Shubham Sharma, Yunfeng Zhang, Jess M. Ros Aliaga, Djallel Bouneffouf, Vinod Muthusamy, Kush R. Varshney |
| 2020 | CEC | Survey on Applications of Multi-Armed and Contextual Bandits. | Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal |
| 2020 | IJCAI | Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. | Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish |
| 2020 | IJCNN | Survey on Automated End-to-End Data Science? | Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray |
| 2019 | AAAI | Incorporating Behavioral Constraints in Online AI Systems. | Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei, Francesca Rossi |
| 2019 | AAAI | Scalable Recollections for Continual Lifelong Learning. | Matthew Riemer, Tim Klinger, Djallel Bouneffouf, Michele Franceschini |
| 2019 | ICML | 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 |
| 2019 | IJCAI | Optimal Exploitation of Clustering and History Information in Multi-armed Bandit. | Djallel Bouneffouf, Srinivasan Parthasarathy, Horst Samulowitz, Martin Wistuba |
| 2019 | IJCAI | Split Q Learning: Reinforcement Learning with Two-Stream Rewards. | Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi |
| 2019 | IJCAI | Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration. | Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi |
| 2018 | ICDM | Contextual Bandit with Adaptive Feature Extraction. | Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Irina Rish |
| 2018 | IJCAI | Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation. | Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei, Francesca Rossi |
| 2018 | IJCNN | Eigenspectrum Shape Based Nystrm Sampling. | Djallel Bouneffouf |
| 2017 | IJCAI | Context Attentive Bandits: Contextual Bandit with Restricted Context. | Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphal Fraud |
| 2016 | CEC | Finite-time analysis of the multi-armed bandit problem with known trend. | Djallel Bouneffouf |
| 2016 | CEC | Contextual bandit algorithm for risk-aware recommender systems. | Djallel Bouneffouf |
| 2016 | IJCNN | Ensemble Minimum Sum of Squared Similarities sampling for Nystrm-based spectral clustering. | Djallel Bouneffouf, Inan Birol |
| 2016 | IJCNN | Theoretical analysis of the Minimum Sum of Squared Similarities sampling for Nystrm-based spectral clustering. | Djallel Bouneffouf, Inan Birol |
| 2015 | IJCAI | Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering. | Djallel Bouneffouf, Inan Birol |
| 2014 | ICONIP | A Neural Networks Committee for the Contextual Bandit Problem. | Robin Allesiardo, Raphal Fraud, Djallel Bouneffouf |
| 2014 | ICONIP | Freshness-Aware Thompson Sampling. | Djallel Bouneffouf |
| 2014 | ICONIP | Contextual Bandit for Active Learning: Active Thompson Sampling. | Djallel Bouneffouf, Romain Laroche, Tanguy Urvoy, Raphal Fraud, Robin Allesiardo |
| 2013 | ICONIP | Risk-Aware Recommender Systems. | Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Ganarski |
| 2013 | ICONIP | Contextual Bandits for Context-Based Information Retrieval. | Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Ganarski |
| 2012 | AINA | Following the User's Interests in Mobile Context-Aware Recommender Systems: The Hybrid-e-greedy Algorithm. | Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Ganarski |
| 2012 | ICONIP | A Contextual-Bandit Algorithm for Mobile Context-Aware Recommender System. | Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Ganarski |
| 2012 | PAKDD | Hybrid-ε-greedy for Mobile Context-Aware Recommender System. | Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Ganarski |
| 2011 | CaiSE | Applying Machine Learning Techniques to Improve User Acceptance on Ubiquitous Environment. | Djallel Bouneffouf |