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2020 – today
- 2023
[c7]Iñigo Urteaga, Moulay-Zaïdane Draïdia, Tomer Lancewicki, Shahram Khadivi:
Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking. ACL (Findings) 2023: 10609-10627- [i6]Baohao Liao, Michael Kozielski, Sanjika Hewavitharana, Jiangbo Yuan, Shahram Khadivi, Tomer Lancewicki:
ITEm: Unsupervised Image-Text Embedding Learning for eCommerce. CoRR abs/2311.02084 (2023) - 2022
- [i5]Iñigo Urteaga, Moulay-Zaïdane Draïdia, Tomer Lancewicki, Shahram Khadivi:
Multi-armed bandits for online optimization of language model pre-training: the use case of dynamic masking. CoRR abs/2203.13151 (2022) - 2021
- [c6]Ahmed Abdulaal
, Tomer Lancewicki:
Real-Time Synchronization in Neural Networks for Multivariate Time Series Anomaly Detection. ICASSP 2021: 3570-3574 - [c5]Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney:
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer. IWSLT 2021: 276-286 - [c4]Ahmed Abdulaal, Zhuanghua Liu, Tomer Lancewicki:
Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization. KDD 2021: 2485-2494 - [i4]Leonard Dahlmann, Tomer Lancewicki:
Deploying a BERT-based Query-Title Relevance Classifier in a Production System: a View from the Trenches. CoRR abs/2108.10197 (2021) - [i3]Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney:
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer. CoRR abs/2109.12950 (2021) - [i2]Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney:
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer. CoRR abs/2109.13097 (2021) - 2020
- [c3]Tomer Lancewicki, Selçuk Köprü:
Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient-based Optimization Methods. ICASSP 2020: 3127-3131
2010 – 2019
- 2019
- [i1]Tomer Lancewicki, Selçuk Köprü:
Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent. CoRR abs/1908.07607 (2019) - 2017
- [c2]Tomer Lancewicki:
Sequential Inverse Approximation of a Regularized Sample Covariance Matrix. ICMLA 2017: 903-907 - 2015
- [c1]Tomer Lancewicki, Benjamin Goodrich, Itamar Arel:
Sequential Covariance-Matrix Estimation with Application to Mitigating Catastrophic Forgetting. ICMLA 2015: 628-633 - 2014
- [j2]Tomer Lancewicki, Mayer E. Aladjem:
Locally multidimensional scaling by creating neighborhoods in diffusion maps. Neurocomputing 139: 382-396 (2014) - [j1]Tomer Lancewicki, Mayer E. Aladjem:
Multi-Target Shrinkage Estimation for Covariance Matrices. IEEE Trans. Signal Process. 62(24): 6380-6390 (2014)
Coauthor Index
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