| 2026 | ACL | ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks. | Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurlie C. Lozano, Pin-Yu Chen |
| 2025 | ICML | Aligning Protein Conformation Ensemble Generation with Physical Feedback. | Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurlie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang |
| 2024 | ACL | NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. | Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurlie C. Lozano, Payel Das, Georgios Kollias |
| 2024 | AISTATS | Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. | Dongxia Wu, Tsuyoshi Id, Georgios Kollias, Jir Navrtil, Aurlie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu |
| 2024 | ICML | Larimar: Large Language Models with Episodic Memory Control. | Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurlie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jir Navrtil, Soham Dan, Pin-Yu Chen |
| 2023 | ICASSP | Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks. | Yonas Sium, Georgios Kollias, Tsuyoshi Id, Payel Das, Naoki Abe, Aurlie C. Lozano, Qi Li |
| 2023 | ICLR | Protein Representation Learning by Geometric Structure Pretraining. | Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurlie C. Lozano, Payel Das, Jian Tang |
| 2022 | AAAI | Directed Graph Auto-Encoders. | Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Id, Aurlie C. Lozano, Naoki Abe |
| 2022 | AISTATS | AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning. | Jihun Yun, Aurlie C. Lozano, Eunho Yang |
| 2019 | ICML | Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. | Jihun Yun, Peng Zheng, Eunho Yang, Aurlie C. Lozano, Aleksandr Y. Aravkin |
| 2017 | ICLR | Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurlie C. Lozano |
| 2017 | ICML | Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity. | Eunho Yang, Aurlie C. Lozano |
| 2017 | IJCAI | Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurlie C. Lozano |
| 2016 | CVPR | Removing Clouds and Recovering Ground Observations in Satellite Image Sequences via Temporally Contiguous Robust Matrix Completion. | Jialei Wang, Peder A. Olsen, Andrew R. Conn, Aurlie C. Lozano |
| 2015 | RECOMB | An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations. | Seunghak Lee, Aurlie C. Lozano, Prabhanjan Kambadur, Eric P. Xing |
| 2014 | ICDM | Orthogonal Matching Pursuit for Sparse Quantile Regression. | Aleksandr Y. Aravkin, Aurlie C. Lozano, Ronny Luss, Prabhanjan Kambadur |
| 2014 | ICML | Elementary Estimators for High-Dimensional Linear Regression. | Eunho Yang, Aurlie C. Lozano, Pradeep Ravikumar |
| 2014 | ICML | Elementary Estimators for Sparse Covariance Matrices and other Structured Moments. | Eunho Yang, Aurlie C. Lozano, Pradeep Ravikumar |
| 2013 | AISTATS | A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions. | Prabhanjan Kambadur, Aurlie C. Lozano |
| 2013 | KDD | Robust sparse estimation of multiresponse regression and inverse covariance matrix via the L2 distance. | Aurlie C. Lozano, Huijing Jiang, Xinwei Deng |
| 2013 | UAI | Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. | Vikas Sindhwani, Ha Quang Minh, Aurlie C. Lozano |
| 2012 | ICML | Multi-level Lasso for Sparse Multi-task Regression. | Aurlie C. Lozano, Grzegorz Swirszcz |
| 2012 | SDM | A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation. | Huijing Jiang, Aurlie C. Lozano, Fei Liu |
| 2010 | ICML | Learning Temporal Causal Graphs for Relational Time-Series Analysis. | Yan Liu, Alexandru Niculescu-Mizil, Aurlie C. Lozano, Yong Lu |
| 2009 | KDD | A data modeling approach to climate change attribution. | Aurlie C. Lozano |
| 2009 | KDD | Grouped graphical Granger modeling methods for temporal causal modeling. | Aurlie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset |
| 2009 | KDD | Spatial-temporal causal modeling for climate change attribution. | Aurlie C. Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan R. M. Hosking, Naoki Abe |
| 2009 | SDM | Proximity-Based Anomaly Detection Using Sparse Structure Learning. | Tsuyoshi Id, Aurlie C. Lozano, Naoki Abe, Yan Liu |
| 2008 | KDD | Multi-class cost-sensitive boosting with p-norm loss functions. | Aurlie C. Lozano, Naoki Abe |
| 2006 | ISIT | Convergence and Consistency of Recursive Boosting. | Aurlie C. Lozano, Sanjeev R. Kulkarni |
| 2005 | ISIT | A wireless network can achieve maximum throughput without each node meeting all others. | Aurlie C. Lozano, Sanjeev R. Kulkarni |
| 2004 | ISIT | Throughput scaling in wireless networks with restricted mobility. | Aurlie C. Lozano, Sanjeev R. Kulkarni, Pramod Viswanath |
| 2002 | DCC | Quantized Frame Expansions In A Wireless Environment. | Aurlie C. Lozano, Jelena Kovacevic, Mike Andrews |