Alexander Lin

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 21

Top Topics

Maximum Likelihood

Change Management

Nonlinear Dynamics

Top Venues

Publications

Alexander Lin, Demba E. Ba
An Efficient Algorithm For Clustered Multi-Task Compressive Sensing. ICASSP (2024)
Alexander Lin, Lucas Monteiro Paes, Sree Harsha Tanneru, Suraj Srinivas, Himabindu Lakkaraju
Word-Level Explanations for Analyzing Bias in Text-to-Image Models. CoRR (2023)
Alexander Lin, Bahareh Tolooshams, Yves Atchadé, Demba Ba
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. CoRR (2023)
Mohammad Al-Fares, Virginia Beauregard, Kevin Grant, Angus Griffith, Jahangir Hasan, Chen Huang, Quan Leng, Jiayao Li, Alexander Lin, Zhuotao Liu, Ahmed Mansy, Bill Martinusen, Nikil Mehta, Jeffrey C. Mogul, Andrew Narver, Anshul Nigham, Melanie Obenberger, Sean Smith, Kurt Steinkraus, Sheng Sun, Edward Thiele, Amin Vahdat
Change Management in Physical Network Lifecycle Automation. USENIX Annual Technical Conference (2023)
Alexander Lin, Demba E. Ba
An Efficient Algorithm for Clustered Multi-Task Compressive Sensing. CoRR (2023)
Autumn Toney-Wails, Kornraphop Kawintiranon, Lisa Singh, Paul-Emmanuel Courtines, Alexander Lin, Haofei Zhang
Investigating Scientific Misinformation Using Different Modes of Learning. SDU@AAAI (2023)
Alexander Lin, Bahareh Tolooshams, Yves Atchadé, Demba E. Ba
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. ICML (2023)
Alexander Lin, Andrew H. Song, Demba E. Ba
Mixture Model Auto-Encoders: Deep Clustering Through Dictionary Learning. ICASSP (2022)
Alexander Lin, Alex Lu
Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images. MLCB (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
Covariance-Free Sparse Bayesian Learning. IEEE Trans. Signal Process. 70 (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. CoRR (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. ICASSP (2022)
Derek Chen, Howard Chen, Yi Yang, Alexander Lin, Zhou Yu
Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems. NAACL-HLT (2021)
Alexander Lin, Andrew H. Song, Demba E. Ba
Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning. CoRR (2021)
Xinping Hu, Yang Miang Goh, Alexander Lin
Educational impact of an Augmented Reality (AR) application for teaching structural systems to non-engineering students. Adv. Eng. Informatics 50 (2021)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
Covariance-Free Sparse Bayesian Learning. CoRR (2021)
Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
Autoregressive Knowledge Distillation through Imitation Learning. CoRR (2020)
Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
Autoregressive Knowledge Distillation through Imitation Learning. EMNLP (1) (2020)
Alexander Lin, Amil Merchant, Suproteem K. Sarkar, Alexander D'Amour
Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models. CD@KDD (2019)
Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. AISTATS (2019)
Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. CoRR (2018)
Daniel Cocuzzo, Alexander Lin, Saadallah Ramadan, Carolyn Mountford, Nirmal Keshava
Algorithms for characterizing brain metabolites in two-dimensional in vivo MR correlation spectroscopy. EMBC (2011)
Peter Stanwell, Philip Siddall, Nirmal Keshava, Daniel Cocuzzo, Saadallah Ramadan, Alexander Lin, David Herbert, Ashley Craig, Yvonne Tran, James W. Middleton, Shiva Gautam, Michael Cousins, Carolyn Mountford
Neuro magnetic resonance spectroscopy using wavelet decomposition and statistical testing identifies biochemical changes in people with spinal cord injury and pain. NeuroImage 53 (2) (2010)