| Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing S Abu-El-Haija, B Perozzi, A Kapoor, N Alipourfard, K Lerman, ... international conference on machine learning, 21-29, 2019 | 1032 | 2019 |
| Multitask learning and benchmarking with clinical time series data H Harutyunyan, H Khachatrian, DC Kale, G Ver Steeg, A Galstyan Scientific data 6 (1), 96, 2019 | 1027 | 2019 |
| Improving generalization by controlling label-noise information in neural network weights H Harutyunyan, K Reing, G Ver Steeg, A Galstyan International Conference on Machine Learning, 4071-4081, 2020 | 63 | 2020 |
| Information-theoretic generalization bounds for black-box learning algorithms H Harutyunyan, M Raginsky, G Ver Steeg, A Galstyan Advances in Neural Information Processing Systems 34, 24670-24682, 2021 | 48 | 2021 |
| Estimating informativeness of samples with Smooth Unique Information H Harutyunyan, A Achille, G Paolini, O Majumder, A Ravichandran, ... International Conference on Learning Representations, 2021 | 28 | 2021 |
| Failure modes of domain generalization algorithms T Galstyan, H Harutyunyan, H Khachatrian, GV Steeg, A Galstyan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| Supervision complexity and its role in knowledge distillation H Harutyunyan, AS Rawat, AK Menon, S Kim, S Kumar arXiv preprint arXiv:2301.12245, 2023 | 12 | 2023 |
| A meta-learning approach to predicting performance and data requirements A Jain, G Swaminathan, P Favaro, H Yang, A Ravichandran, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Fast structure learning with modular regularization G Ver Steeg, H Harutyunyan, D Moyer, A Galstyan Advances in Neural Information Processing Systems 32, 2019 | 8 | 2019 |
| Disentangled representations via synergy minimization G Ver Steeg, R Brekelmans, H Harutyunyan, A Galstyan 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017 | 5 | 2017 |
| Formal limitations of sample-wise information-theoretic generalization bounds H Harutyunyan, G Ver Steeg, A Galstyan 2022 IEEE Information Theory Workshop (ITW), 440-445, 2022 | 4 | 2022 |
| Efficient covariance estimation from temporal data H Harutyunyan, D Moyer, H Khachatrian, GV Steeg, A Galstyan arXiv preprint arXiv:1905.13276, 2019 | 4 | 2019 |
| Combining cnn and rnn for spoken language identification H Harutyunyan, H Khachatrian YerevaNN Blog on neural networks 11, 2016 | 4 | 2016 |
| Identifying geopolitical event precursors using attention-based LSTMs KSMT Hossain, H Harutyunyan, Y Ning, B Kennedy, N Ramakrishnan, ... Frontiers in Artificial Intelligence 5, 893875, 2022 | 3 | 2022 |
| Identifying and disentangling spurious features in pretrained image representations R Darbinyan, H Harutyunyan, AH Markosyan, H Khachatrian arXiv preprint arXiv:2306.12673, 2023 | 2 | 2023 |
| A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs AS Rawat, V Sadhanala, A Rostamizadeh, A Chakrabarti, W Jitkrittum, ... arXiv preprint arXiv:2410.18779, 2024 | 1 | 2024 |
| Relaxed recursive transformers: Effective parameter sharing with layer-wise lora S Bae, A Fisch, H Harutyunyan, Z Ji, S Kim, T Schuster arXiv preprint arXiv:2410.20672, 2024 | | 2024 |
| Mimetic Initialization Helps State Space Models Learn to Recall A Trockman, H Harutyunyan, JZ Kolter, S Kumar, S Bhojanapalli arXiv preprint arXiv:2410.11135, 2024 | | 2024 |
| In-context learning in presence of spurious correlations H Harutyunyan, R Darbinyan, S Karapetyan, H Khachatrian arXiv preprint arXiv:2410.03140, 2024 | | 2024 |
| On information captured by neural networks: connections with memorization and generalization H Harutyunyan arXiv preprint arXiv:2306.15918, 2023 | | 2023 |
Aram GalstyanUSC ISI & Amazon AGIVerified email at isi.edu
