Alexander Lin - RankMe

24 papers A* 1A 1Misc 3Journal 11Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	A Deep Learning Approach for Placing Magnetic Resonance Spectroscopy Voxels in Brain Tumors. MICCAI (3) Sangyoon Lee, Francesca Branzoli, Thanh Nguyen, Ovidiu C. Andronesi, Alexander Lin, Roberto Liserre, Gerd Melkus, Clark Chen, Malgorzata Marjanska, Patrick J. Bolan
2024	Misc	`conf`	An Efficient Algorithm For Clustered Multi-Task Compressive Sensing. ICASSP Alexander Lin, Demba E. Ba
2023	J	`jnl`	An Efficient Algorithm for Clustered Multi-Task Compressive Sensing. CoRR Alexander Lin, Demba E. Ba
2023	—	`conf`	Change Management in Physical Network Lifecycle Automation. USENIX ATC 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
2023	—	`conf`	Investigating Scientific Misinformation Using Different Modes of Learning. SDU@AAAI Autumn Toney-Wails, Kornraphop Kawintiranon, Lisa Singh, Paul-Emmanuel Courtines, Alexander Lin, Haofei Zhang
2023	A*	`conf`	Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. ICML Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba
2023	J	`jnl`	Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. CoRR Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba
2023	J	`jnl`	Word-Level Explanations for Analyzing Bias in Text-to-Image Models. CoRR Alexander Lin, Lucas Monteiro Paes, Sree Harsha Tanneru, Suraj Srinivas, Himabindu Lakkaraju
2022	J	`jnl`	Covariance-Free Sparse Bayesian Learning. IEEE Trans. Signal Process. Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
2022	Misc	`conf`	High-Dimensional Sparse Bayesian Learning without Covariance Matrices. ICASSP Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
2022	J	`jnl`	High-Dimensional Sparse Bayesian Learning without Covariance Matrices. CoRR Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
2022	—	`conf`	Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images. MLCB Alexander Lin, Alex Lu
2022	Misc	`conf`	Mixture Model Auto-Encoders: Deep Clustering Through Dictionary Learning. ICASSP Alexander Lin, Andrew H. Song, Demba E. Ba
2021	—	`conf`	Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems. NAACL-HLT Derek Chen, Howard Chen, Yi Yang, Alexander Lin, Zhou Yu
2021	J	`jnl`	Covariance-Free Sparse Bayesian Learning. CoRR Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
2021	J	`jnl`	Educational impact of an Augmented Reality (AR) application for teaching structural systems to non-engineering students. Adv. Eng. Informatics Xinping Hu, Yang Miang Goh, Alexander Lin
2021	J	`jnl`	Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning. CoRR Alexander Lin, Andrew H. Song, Demba E. Ba
2020	—	`conf`	Autoregressive Knowledge Distillation through Imitation Learning. EMNLP (1) Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
2020	J	`jnl`	Autoregressive Knowledge Distillation through Imitation Learning. CoRR Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
2019	A	`conf`	Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. AISTATS Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba
2019	—	`conf`	Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models. CD@KDD Alexander Lin, Amil Merchant, Suproteem K. Sarkar, Alexander D'Amour
2018	J	`jnl`	Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. CoRR Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba
2011	—	`conf`	Algorithms for characterizing brain metabolites in two-dimensional in vivo MR correlation spectroscopy. EMBC Daniel Cocuzzo, Alexander Lin, Saadallah Ramadan, Carolyn Mountford, Nirmal Keshava
2010	J	`jnl`	Neuro magnetic resonance spectroscopy using wavelet decomposition and statistical testing identifies biochemical changes in people with spinal cord injury and pain. NeuroImage 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