activity
20172026
most citedRegularization of the Kernel Matrix via Covariance Matrix Shrinkage Estimation

3 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

STARIXNet: Multivariate and Multi-attribute Deep Learning Approach to Real-Time Resource Allocation in Cloud Platforms

Ahmed Abdulaal, Maruf Aytekin, Thilaga kumaran Srinivasan +1

Intelligent scaling of microservices in cloud platforms is crucial for mitigating escalating compute costs while avoiding service disruptions. Current solutions are limited to the…

cs.CV2023

ITEm: Unsupervised Image-Text Embedding Learning for eCommerce

Baohao Liao, Michael Kozielski, Sanjika Hewavitharana +3

Product embedding serves as a cornerstone for a wide range of applications in eCommerce. The product embedding learned from multiple modalities shows significant improvement over t…

cs.CL2022

Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking

Iñigo Urteaga, Moulay-Zaïdane Draïdia, Tomer Lancewicki +1

We design and evaluate a Bayesian optimization framework for resource efficient pre-training of Transformer-based language models (TLMs). TLM pre-training requires high computation…

cs.CL2021★ 1 cited

Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer

Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang +4

Pivot-based neural machine translation (NMT) is commonly used in low-resource setups, especially for translation between non-English language pairs. It benefits from using high res…

cs.CL2021★ 2 cited

Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer

Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang +4

Complex natural language applications such as speech translation or pivot translation traditionally rely on cascaded models. However, cascaded models are known to be prone to error…

cs.CL2021

Deploying a BERT-based Query-Title Relevance Classifier in a Production System: a View from the Trenches

Leonard Dahlmann, Tomer Lancewicki

The Bidirectional Encoder Representations from Transformers (BERT) model has been radically improving the performance of many Natural Language Processing (NLP) tasks such as Text C…