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Fast Graph Learning with Unique Optimal Solutions

Feb 21, 2021
Sami Abu-El-Haija, Valentino Crespi, Greg Ver Steeg, Aram Galstyan


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Improved Brain Age Estimation with Slice-based Set Networks

Feb 09, 2021
Umang Gupta, Pradeep K. Lam, Greg Ver Steeg, Paul M. Thompson

* To appear at IEEE International Symposium on Biomedical Imaging 2021 (ISBI 2021). Code is available at https://git.io/JtazG 

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Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning

Feb 08, 2021
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan

* To appear in ICLR 2021 

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Likelihood Ratio Exponential Families

Jan 15, 2021
Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg

* NeurIPS Workshop on Deep Learning through Information Geometry 

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Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation

Jan 11, 2021
Umang Gupta, Aaron Ferber, Bistra Dilkina, Greg Ver Steeg

* To appear in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21) 

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Annealed Importance Sampling with q-Paths

Dec 14, 2020
Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

* NeurIPS Workshop on Deep Learning through Information Geometry (Best Paper Award) 

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Compressing Deep Neural Networks via Layer Fusion

Jul 29, 2020
James O' Neill, Greg Ver Steeg, Aram Galstyan


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Robust Classification under Class-Dependent Domain Shift

Jul 10, 2020
Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan

* Accepted at ICML 2020 workshop on Uncertainty and Robustness in Deep Learning 

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All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Jul 01, 2020
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

* ICML 2020 

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Latent Embeddings of Point Process Excitations

Jun 02, 2020
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan

* 8 pages 

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Overview of Scanner Invariant Representations

May 29, 2020
Daniel Moyer, Greg Ver Steeg, Paul M. Thompson

* Accepted as a short paper in MIDL 2020. In accordance with the MIDL 2020 Call for Papers, this short paper is an overview of an already published work arXiv:1904.05375, and was submitted to MIDL in order to allow presentation and discussion at the meeting 

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Event Cartography: Latent Point Process Embeddings

May 05, 2020
Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan

* 8 pages 

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Improving Generalization by Controlling Label-Noise Information in Neural Network Weights

Feb 19, 2020
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan


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Discovery and Separation of Features for Invariant Representation Learning

Dec 02, 2019
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan

* 10 pages, 3 figures 

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Invariant Representations through Adversarial Forgetting

Nov 20, 2019
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan

* To appear in Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20) 

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Nearly-Unsupervised Hashcode Representations for Relation Extraction

Sep 09, 2019
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo Cecchi

* Proceedings of EMNLP-19 

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Efficient Covariance Estimation from Temporal Data

May 30, 2019
Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan


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MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing

May 28, 2019
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan


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MixHop: Higher-Order Graph Convolution Architectures via Sparsified Neighborhood Mixing

Apr 30, 2019
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan

* International Conference on Machine Learning, 2019 

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Exact Rate-Distortion in Autoencoders via Echo Noise

Apr 15, 2019
Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg


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Scanner Invariant Representations for Diffusion MRI Harmonization

Apr 10, 2019
Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax, Paul M. Thompson


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Identifying and Analyzing Cryptocurrency Manipulations in Social Media

Feb 04, 2019
Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Fred Morstatter, Greg Ver Steeg, Aram Galstyan


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Invariant Representations without Adversarial Training

Nov 04, 2018
Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan

* NIPS 2018 camera-ready version 

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Kernelized Hashcode Representations for Biomedical Relation Extraction

Oct 31, 2018
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo Cecchi, Shuyang Gao

* To appear in the proceedings of conference, AAAI-19 

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Dialogue Modeling Via Hash Functions

Oct 18, 2018
Sahil Garg, Irina Rish, Guillermo Cecchi, Shuyang Gao, Palash Goyal, Sarik Ghazarian, Greg Ver Steeg, Aram Galstyan

* Presented at IJCAI-ICML 2018 Workshops. The paper is revised significantly with an addition of elaborate experimental analysis 

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Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge

Sep 03, 2018
Ryan J. Gallagher, Kyle Reing, David Kale, Greg Ver Steeg

* Transactions of the Association for Computational Linguistics (TACL), Vol. 5, 2017 
* 21 pages, 7 figures. 2018/09/03: Updated citation for HA/DR dataset 

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