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ORCIDHrayr Harutyunyan
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2020 – today
- 2024
[i14]Hrayr Harutyunyan, Rafayel Darbinyan, Samvel Karapetyan, Hrant Khachatrian:
In-context Learning in Presence of Spurious Correlations. CoRR abs/2410.03140 (2024)- 2023
- [c10]Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele, Ashwin Swaminathan, Stefano Soatto:
A Meta-Learning Approach to Predicting Performance and Data Requirements. CVPR 2023: 3623-3632 - [c9]Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar:
Supervision Complexity and its Role in Knowledge Distillation. ICLR 2023 - [i13]Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar:
Supervision Complexity and its Role in Knowledge Distillation. CoRR abs/2301.12245 (2023) - [i12]Achin Jain, Gurumurthy Swaminathan, Paolo Favaro, Hao Yang, Avinash Ravichandran, Hrayr Harutyunyan, Alessandro Achille, Onkar Dabeer, Bernt Schiele
, Ashwin Swaminathan, Stefano Soatto:
A Meta-Learning Approach to Predicting Performance and Data Requirements. CoRR abs/2303.01598 (2023) - [i11]Rafayel Darbinyan, Hrayr Harutyunyan, Aram H. Markosyan, Hrant Khachatrian:
Identifying and Disentangling Spurious Features in Pretrained Image Representations. CoRR abs/2306.12673 (2023) - [i10]Hrayr Harutyunyan:
On information captured by neural networks: connections with memorization and generalization. CoRR abs/2306.15918 (2023) - 2022
- [j1]K. S. M. Tozammel Hossain, Hrayr Harutyunyan, Yue Ning, Brendan Kennedy, Naren Ramakrishnan, Aram Galstyan:
Identifying geopolitical event precursors using attention-based LSTMs. Frontiers Artif. Intell. 5 (2022) - [c8]Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Failure Modes of Domain Generalization Algorithms. CVPR 2022: 19055-19064 - [c7]Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
Formal limitations of sample-wise information-theoretic generalization bounds. ITW 2022: 440-445 - [i9]Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
Formal limitations of sample-wise information-theoretic generalization bounds. CoRR abs/2205.06915 (2022) - 2021
- [c6]Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto:
Estimating informativeness of samples with Smooth Unique Information. ICLR 2021 - [c5]Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan:
Information-theoretic generalization bounds for black-box learning algorithms. NeurIPS 2021: 24670-24682 - [i8]Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto:
Estimating informativeness of samples with Smooth Unique Information. CoRR abs/2101.06640 (2021) - [i7]Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan:
Information-theoretic generalization bounds for black-box learning algorithms. CoRR abs/2110.01584 (2021) - [i6]Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Failure Modes of Domain Generalization Algorithms. CoRR abs/2111.13733 (2021) - 2020
- [c4]Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Improving generalization by controlling label-noise information in neural network weights. ICML 2020: 4071-4081 - [i5]Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan:
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights. CoRR abs/2002.07933 (2020)
2010 – 2019
- 2019
- [c3]Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan:
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. ICML 2019: 21-29 - [c2]Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan:
Fast structure learning with modular regularization. NeurIPS 2019: 15567-15577 - [i4]Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Hrayr Harutyunyan, Nazanin Alipourfard, Kristina Lerman, Greg Ver Steeg, Aram Galstyan:
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. CoRR abs/1905.00067 (2019) - [i3]Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan:
Efficient Covariance Estimation from Temporal Data. CoRR abs/1905.13276 (2019) - 2017
- [c1]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled representations via synergy minimization. Allerton 2017: 180-187 - [i2]Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Aram Galstyan:
Multitask Learning and Benchmarking with Clinical Time Series Data. CoRR abs/1703.07771 (2017) - [i1]Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan:
Disentangled Representations via Synergy Minimization. CoRR abs/1710.03839 (2017)
Coauthor Index
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