ServiceNow Research

Issam H. Laradji

Issam H. Laradji

Research Manager

AI Frontier Research

Issam Laradji is a research scientist at ServiceNow Research who focuses on methods that minimize the amount of labels required to efficiently train machine learning models. He completed his postdoc at McGill’s Graphics lab and completed his PhD at the Machine Learning lab of University of British Columbia. His current topics of interest are natural language processing, computer vision (both 2D and 3D), and optimization. On the side, he continuously works on Haven-AI, a toolkit to help people build end-to-end deep learning methods and manage large-scale experiments.

Interests
  • Low Supervision
  • Summarization
  • Text Classification
  • Optimization

Publications

Fast Convergence of Softmax Policy Mirror Ascent. International Conference on Artificial Intelligence and Statistics (AISTATS),  2025.

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Workflow discovery in low data regimes. Workshop at the International Conference on Machine Learning (ICML),  2023.

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Affinity Learning With Blind-spot Self-supervision for Image Denoising. International Conference on Acoustics, Speech and Signal Processing (ICASSP),  2023.

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Countering Language Drift with KL Regularization. Workshop on Interactive Learning for Natural Language Processing (NeurIPS Workshop),  2022.

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Competition exacerbates Language Drift. Machine Learning and the Evolution of Language (JCoLE Workshop),  2022.

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Neural Point Light Fields. Computer Vision and Pattern Recognition (CVPR),  2022.

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