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![AT3.jpg](https://static.wixstatic.com/media/601e73_f518101a31c54081b817e34911868e28~mv2.jpg/v1/crop/x_50,y_0,w_657,h_700/fill/w_200,h_214,al_c,q_80,usm_0.66_1.00_0.01,enc_avif,quality_auto/AT3.jpg)
Ali Tajer
Professor
Electrical, Computer, and Systems Engineering
Rensselaer Polytechnic Institute
(518) 276-8237
6040 Jonsson Engineering Center (JEC)
110 8th Street, Troy, NY 12180
[J64] | B. Varıcı, E. Acartürk, K. Shanmugam, and A. Tajer. Score-based Causal Representation Learning from Interventions. | |
[J63] | A. Mukherjee and A. Tajer. Efficient Best Arm Identification in Stochastic Bandits: Beyond β−optimality. IEEE Transactions on Information Theory (to appear) | |
[C101] | Z. Yan and A. Tajer. Linear Causal Bandits: Unknown Graph and Soft Interventions. In Proc. Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2024. | |
[C100] | B. Varici, D. Katz-Rogozhniko, D. Wei, P. Sattiger, A. Tajer. Interventional Causal Discovery in a Mixture of DAGs. in Proc. Conference on Neural Information Processing Systems (NeurIPS). Vancounver, Canada, December 2024. | |
[C99] | E. Acartürk. B. Varıcı, K. Shanmugam, and A. Tajer. Sample Complexity of Interventional Causal Representation Learning. In Proc. Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2024. | |
[C98] | B. Varıcı, E. Acartürk, K. Shanmugam, and A. Tajer. Linear Causal Representation Learning from Unknown Multi-node Interventions. In Proc. Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2024. | |
[J60] | P. N. Karthik, V. Y. F. Tan, A. Mukherjee, and A. Tajer. Optimal Best Restless Markov Arm Identification with Fixed Confidence, IEEE Transactions on Information Theory, 70(10):7349–7384, October 2024. | |
[C97] | A. Mukherjee and A. Tajer. BAI in Exponential Family: Efficiency and Optimality. In Proc. IEEE International Symposium on Information Theory (ISIT), Athens, Greece, July 2024. | |
[C96] | Z. Yan, A. Mukherjee, B. Varıcı, and A. Tajer. Improved Bound for Robust Causal Bandits with Linear Models. In Proc. IEEE International Symposium on Information Theory (ISIT), Athens, Greece, July 2024. | |
[C95] | B. Varıcı, E. Acartürk, K. Shanmugam,and A. Tajer. General Identifiability and Achievability for Causal Representation Learning. In International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, May 2024. | |
[C94] | Z. Yan, D. Wei, D. Katz-Rogozhnikov, P. Sattigeri, and A. Tajer. General Causal Bandits: General Causal Models and Interventions. In International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, May 2024. | |
[J59] | Z. Yan, B. Varıcı, A. Mukherjee, and A. Tajer. Robust Causal Bandits for Linear Models, Journal of Selected Areas in Information Theory, 5:78 – 93, March 2024. | |
[C93] | B. Varıcı, E. Acartürk, K. Shanmugam, and A. Tajer. Score-based Causal Representation Learning from Interventions: Nonparametric Identifiability. In Proc. Conference on Neural Information Processing Systems (NeurIPS) – Workshop on Causal Representation Learning, New Orleans, LA, December 2023. | |
[J57] | B. Varıcı, D. Katz-Rogozhnikov, A. Tajer, D. Wei, and P. Sattigeri. Separability Analysis for Causal Discovery in Mixture of DAGs, Transactions on Machine Learning Research, October 2023. | |
[C92] | J. Zhang, H. Chao, A. Dhurandhar, P.-Y. Chen, A. Tajer, Y. Xu, and P. Yan. Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation. In Proc. International Conference on Medical Image Computing and Computer Assisted Intervention, Vancouver, Canada, October 2023. | |
[J56] | B. Varıcı, K. Shanmugam, P. Sattigeri, and A. Tajer. Causal Bandits for Linear Structural Equation Models. Journal of Machine Learning Research, September 2023. | |
[J55] | A. Mukherjee and A. Tajer. SPRT-based Efficient Best Arm Identification in Stochastic Bandits. Journal of Selected Areas in Information Theory, 4:128 – 143, June 2023. | |
[C91] | J. Zhang, H. Chao, A. Dhurandhar, P.-Y. Chen, A. Tajer, Y. Xu, and P. Yan. When Neural Networks Fail to Generalize? A Model Sensitivity Perspective. In Proc. AAAI Conference on Artificial Intelligence, Washington, D.C., February 2023. | |
[J54] | S. Sihag and A. Tajer. Estimating structurally similar graphical models. IEEE Transactions on Information Theory, 69(2):1093–1124, Februrary 2023 | |
[J51] | S. Sihag, A. Tajer, and U. Mitra. Adaptive graph-constrained group testing. IEEE Transactions on Signal Processing, 70:381 – 396, 2022. |
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