b'Ali Ghodsi'

research

∙ 05/25/2022

Towards Understanding Label Regularization for Fine-tuning Pre-trained Language Models

Knowledge Distillation (KD) is a prominent neural model compression tech...

Ivan Kobyzev, et al. ∙

research

∙ 05/14/2022

The Sky Above The Clouds

Technology ecosystems often undergo significant transformations as they ...

Sarah Chasins, et al. ∙

research

∙ 03/17/2022

When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation

Data Augmentation (DA) is known to improve the generalizability of deep ...

Ehsan Kamalloo, et al. ∙

research

∙ 10/16/2021

Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher

With ever growing scale of neural models, knowledge distillation (KD) at...

Mehdi Rezagholizadeh, et al. ∙

research

∙ 09/21/2021

Knowledge Distillation with Noisy Labels for Natural Language Understanding

Knowledge Distillation (KD) is extensively used to compress and deploy l...

Shivendra Bhardwaj, et al. ∙

research

∙ 09/13/2021

KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation

The development of over-parameterized pre-trained language models has ma...

Marzieh S. Tahaei, et al. ∙

research

∙ 09/13/2021

How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding

Knowledge Distillation (KD) is a model compression algorithm that helps ...

Tianda Li, et al. ∙

research

∙ 06/27/2021

Legendre Deep Neural Network (LDNN) and its application for approximation of nonlinear Volterra Fredholm Hammerstein integral equations

Various phenomena in biology, physics, and engineering are modeled by di...

Zeinab Hajimohammadi, et al. ∙

research

∙ 06/27/2021

SymbolicGPT: A Generative Transformer Model for Symbolic Regression

Symbolic regression is the task of identifying a mathematical expression...

Mojtaba Valipour, et al. ∙

research

∙ 05/28/2021

Not Far Away, Not So Close: Sample Efficient Nearest Neighbour Data Augmentation via MiniMax

In Natural Language Processing (NLP), finding data augmentation techniqu...

Ehsan Kamalloo, et al. ∙

research

∙ 04/14/2021

Annealing Knowledge Distillation

Significant memory and computational requirements of large deep neural n...

Aref Jafari, et al. ∙

research

∙ 11/12/2020

Symbolically Solving Partial Differential Equations using Deep Learning

We describe a neural-based method for generating exact or approximate so...

Maysum Panju, et al. ∙

research

∙ 11/04/2020

A Neuro-Symbolic Method for Solving Differential and Functional Equations

When neural networks are used to solve differential equations, they usua...

Maysum Panju, et al. ∙

research

∙ 09/22/2020

Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey

Stochastic Neighbor Embedding (SNE) is a manifold learning and dimension...

Benyamin Ghojogh, et al. ∙

research

∙ 09/17/2020

Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey

Multidimensional Scaling (MDS) is one of the first fundamental manifold ...

Benyamin Ghojogh, et al. ∙

research

∙ 06/30/2020

Segmentation Approach for Coreference Resolution Task

In coreference resolution, it is important to consider all members of a ...

Aref Jafari, et al. ∙

research

∙ 04/17/2019

DeepNovoV2: Better de novo peptide sequencing with deep learning

We introduce DeepNovoV2, the state-of-the-art neural networks based mode...

Rui Qiao, et al. ∙

research

∙ 12/18/2018

Deep Variational Sufficient Dimensionality Reduction

We consider the problem of sufficient dimensionality reduction (SDR), wh...

Ershad Banijamali, et al. ∙

research

∙ 11/07/2018

SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections

Supervised dimensionality reduction strategies have been of great intere...

Amir-Hossein Karimi, et al. ∙

research

∙ 07/23/2018

Text Classification based on Multiple Block Convolutional Highways

In the Text Classification areas of Sentiment Analysis, Subjectivity/Obj...

Seyed Mahdi Rezaeinia, et al. ∙

research

∙ 12/15/2017

A Berkeley View of Systems Challenges for AI

With the increasing commoditization of computer vision, speech recogniti...

Ion Stoica, et al. ∙

research

∙ 11/24/2017

JADE: Joint Autoencoders for Dis-Entanglement

The problem of feature disentanglement has been explored in the literatu...

Ershad Banijamali, et al. ∙

research

∙ 11/23/2017

Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis

Sentiment analysis is one of the well-known tasks and fast growing resea...

Seyed Mahdi Rezaeinia, et al. ∙

research

∙ 08/25/2017

Deep Structure for end-to-end inverse rendering

Inverse rendering in a 3D format denoted to recovering the 3D properties...

Shima Kamyab, et al. ∙

research

∙ 04/07/2017

Fast Spectral Clustering Using Autoencoders and Landmarks

In this paper, we introduce an algorithm for performing spectral cluster...

Ershad Banijamali, et al. ∙

research

∙ 02/10/2017

Generative Mixture of Networks

A generative model based on training deep architectures is proposed. The...

Ershad Banijamali, et al. ∙

research

∙ 04/25/2016

Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion

In this paper, a novel semi-supervised dictionary learning and sparse re...

Mehrdad J. Gangeh, et al. ∙

research

∙ 03/06/2015

On the Invariance of Dictionary Learning and Sparse Representation to Projecting Data to a Discriminative Space

In this paper, it is proved that dictionary learning and sparse represen...

Mehrdad J. Gangeh, et al. ∙

research

∙ 02/20/2015

Supervised Dictionary Learning and Sparse Representation-A Review

Dictionary learning and sparse representation (DLSR) is a recent and suc...

Mehrdad J. Gangeh, et al. ∙

research

∙ 12/24/2013

A Fast Greedy Algorithm for Generalized Column Subset Selection

This paper defines a generalized column subset selection problem which i...

Ahmed K. Farahat, et al. ∙

research

∙ 07/12/2012

Supervised Texture Classification Using a Novel Compression-Based Similarity Measure

Supervised pixel-based texture classification is usually performed in th...

Mehrdad J. Gangeh, et al. ∙

research

∙ 07/10/2012

Kernelized Supervised Dictionary Learning

In this paper, we propose supervised dictionary learning (SDL) by incorp...

Mehrdad J. Gangeh, et al. ∙

Ali Ghodsi

Featured Co-authors