Publications by Rabeeh Karimi Mahabadi

Improving Generalization of Pretrained Language Models

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

EPFL2023

PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models

Rabeeh Karimi Mahabadi

Current methods for few-shot fine-tuning of pretrained masked language models (PLMs) require carefully engineered prompts and verbalizers for each new task to convert examples into a cloze-format that the PLM can score. In this work, we propose PERFECT, a ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

PARSINLU: A Suite of Language Understanding Challenges for Persian

Rabeeh Karimi Mahabadi

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of the wid ...

2021

End-to-End Bias Mitigation by Modelling Biases in Corpora

James Henderson, Rabeeh Karimi Mahabadi

2020

A Learning-Based Framework for Quantized Compressed Sensing

Volkan Cevher, Rabeeh Karimi Mahabadi, Junhong Lin

Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...

IEEE Institute of Electrical and Electronics Engineers2019

Real-time DCT Learning-based Reconstruction of Neural Signals

Volkan Cevher, Cosimo Aprile, Rabeeh Karimi Mahabadi

Wearable and implantable body sensor network systems are one of the key technologies for continuous monitoring of patient’s vital health status such as temperature and blood pressure, and brain activity. Such devices are critical for early detection of eme ...

IEEE2018

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization

Volkan Cevher, Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Ya-Ping Hsieh, Yu-Chun Kao

We study convex optimization problems that feature low-rank matrix solutions. In such scenarios, non-convex methods offer significant advantages over convex methods due to their lower space complexity as well as faster convergence speed. Moreover, many of ...

2018

Learning-Based Compressive MRI

Volkan Cevher, Baran Gözcü, Yen-Huan Li, Rabeeh Karimi Mahabadi, Jonathan Mark Scarlett

In the area of magnetic resonance imaging (MRI), an extensive range of non-linear reconstruction algorithms have been proposed that can be used with general Fourier subsampling patterns. However, the design of these subsampling patterns has typically been ...

Institute of Electrical and Electronics Engineers2018

Scalable sparse covariance estimation via self-concordance

Volkan Cevher, Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran Dinh

We consider the class of convex minimization problems, composed of a self-concordant function, such as the logdet metric, a convex data fidelity term h and, a regularizing -- possibly non-smooth -- function g. This type of problems have recently attracted ...

2014