Ali Ghodsi

Affiliations:
  • University of Waterloo


According to our database1, Ali Ghodsi authored at least 104 papers between 2002 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA.
CoRR, 2022

Spectral, Probabilistic, and Deep Metric Learning: Tutorial and Survey.
CoRR, 2022

When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Generative locally linear embedding: A module for manifold unfolding and visualization.
Softw. Impacts, 2021

Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices.
Nat. Mach. Intell., 2021

Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides.
Medical Image Anal., 2021

A new approach to the numerical solution of Fredholm integral equations using least squares-support vector regression.
Math. Comput. Simul., 2021

Supervised discriminative dimensionality reduction by learning multiple transformation operators.
Expert Syst. Appl., 2021

Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey.
CoRR, 2021

Sufficient Dimension Reduction for High-Dimensional Regression and Low-Dimensional Embedding: Tutorial and Survey.
CoRR, 2021

Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher.
CoRR, 2021

KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey.
CoRR, 2021

KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation.
CoRR, 2021

How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding.
CoRR, 2021

Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey.
CoRR, 2021

Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey.
CoRR, 2021

Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey.
CoRR, 2021

Unified Framework for Spectral Dimensionality Reduction, Maximum Variance Unfolding, and Kernel Learning By Semidefinite Programming: Tutorial and Survey.
CoRR, 2021

Legendre Deep Neural Network (LDNN) and its application for approximation of nonlinear Volterra Fredholm Hammerstein integral equations.
CoRR, 2021

SymbolicGPT: A Generative Transformer Model for Symbolic Regression.
CoRR, 2021

Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey.
CoRR, 2021

Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey.
CoRR, 2021

Generative Locally Linear Embedding.
CoRR, 2021

Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey.
CoRR, 2021

CNN and Deep Sets for End-to-End Whole Slide Image Representation Learning.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Universal-KD: Attention-based Output-Grounded Intermediate Layer Knowledge Distillation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

RW-KD: Sample-wise Loss Terms Re-Weighting for Knowledge Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

How to Select One Among All ? An Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Annealing Knowledge Distillation.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Knowledge Distillation with Noisy Labels for Natural Language Understanding.
Proceedings of the Seventh Workshop on Noisy User-generated Text, 2021

Not Far Away, Not So Close: Sample Efficient Nearest Neighbour Data Augmentation via MiniMax.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Discriminant component analysis via distance correlation maximization.
Pattern Recognit., 2020

Locally Linear Embedding and its Variants: Tutorial and Survey.
CoRR, 2020

Symbolically Solving Partial Differential Equations using Deep Learning.
CoRR, 2020

A Neuro-Symbolic Method for Solving Differential and Functional Equations.
CoRR, 2020

Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey.
CoRR, 2020

Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey.
CoRR, 2020

Segmentation Approach for Coreference Resolution Task.
CoRR, 2020

2019
Sentiment analysis based on improved pre-trained word embeddings.
Expert Syst. Appl., 2019

DeepNovoV2: Better de novo peptide sequencing with deep learning.
CoRR, 2019

2018
Deep Variational Sufficient Dimensionality Reduction.
CoRR, 2018

SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections.
CoRR, 2018

Text Classification based on Multiple Block Convolutional Highways.
CoRR, 2018

Localization and classification of cell nuclei in post-neoadjuvant breast cancer surgical specimen using fully convolutional networks.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018

Distance Correlation Autoencoder.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Nonnegative Matrix Factorization Using Autoencoders And Exponentiated Gradient Descent.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Robust Locally-Linear Controllable Embedding.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Fast and Scalable Feature Selection for Gene Expression Data Using Hilbert-Schmidt Independence Criterion.
IEEE ACM Trans. Comput. Biol. Bioinform., 2017

Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection.
Eng. Appl. Artif. Intell., 2017

Disentangling Dynamics and Content for Control and Planning.
CoRR, 2017

JADE: Joint Autoencoders for Dis-Entanglement.
CoRR, 2017

Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis.
CoRR, 2017

Deep Structure for end-to-end inverse rendering.
CoRR, 2017

Synthesizing Deep Neural Network Architectures using Biological Synaptic Strength Distributions.
CoRR, 2017

Generative mixture of networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Discovery Radiomics via a Mixture of Deep ConvNet Sequencers for Multi-parametric MRI Prostate Cancer Classification.
Proceedings of the Image Analysis and Recognition - 14th International Conference, 2017

Fast Spectral Clustering Using Autoencoders and Landmarks.
Proceedings of the Image Analysis and Recognition - 14th International Conference, 2017

2016
Semi-Supervised Representation Learning based on Probabilistic Labeling.
CoRR, 2016

Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion.
Proceedings of the Image Analysis and Recognition - 13th International Conference, 2016

2015
Greedy column subset selection for large-scale data sets.
Knowl. Inf. Syst., 2015

Supervised Dictionary Learning and Sparse Representation-A Review.
CoRR, 2015

Learning the Structure of Sum-Product Networks via an SVD-based Algorithm.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis.
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Kolmogorov complexity vector: A novel data representation.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Multiview Supervised Dictionary Learning in Speech Emotion Recognition.
IEEE ACM Trans. Audio Speech Lang. Process., 2014

Minimizing the Discrepancy Between Source and Target Domains by Learning Adapting Components.
J. Comput. Sci. Technol., 2014

2013
Kernelized Supervised Dictionary Learning.
IEEE Trans. Signal Process., 2013

Discriminative functional analysis of human movements.
Pattern Recognit. Lett., 2013

Efficient greedy feature selection for unsupervised learning.
Knowl. Inf. Syst., 2013

Determining Protein Structures from NOESY Distance Constraints by Semidefinite Programming.
J. Comput. Biol., 2013

A Fast Greedy Algorithm for Generalized Column Subset Selection.
CoRR, 2013

Distributed Column Subset Selection on MapReduce.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Information-centric networking - Ready for the real world? (Dagstuhl Seminar 12361).
Dagstuhl Reports, 2012

Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Protein Structure by Semidefinite Facial Reduction.
Proceedings of the Research in Computational Molecular Biology, 2012

Low Dimensional Localized Clustering (LDLC).
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Adapting Component Analysis.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Supervised Texture Classification Using a Novel Compression-Based Similarity Measure.
Proceedings of the Computer Vision and Graphics - International Conference, 2012

2011
Guided Locally Linear Embedding.
Pattern Recognit. Lett., 2011

Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds.
Pattern Recognit., 2011

A novel greedy algorithm for Nyström approximation.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Robust locally linear embedding using penalty functions.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Parameter selection for smoothing splines using Stein's Unbiased Risk Estimator.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Dictionary Learning in Texture Classification.
Proceedings of the Image Analysis and Recognition - 8th International Conference, 2011

An Efficient Greedy Method for Unsupervised Feature Selection.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010
Learning an Affine Transformation for Non-linear Dimensionality Reduction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Rare Class Classification by Support Vector Machine.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Conformal Mapping by Computationally Efficient Methods.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Towards Robust Peer Counting.
Proceedings of the Proceedings P2P 2009, 2009

2008
Scalable Action Respecting Embedding.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Nonnegative matrix factorization via rank-one downdate.
Proceedings of the Machine Learning, 2008

Distance Metric Learning Versus Fisher Discriminant Analysis.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Improving Embeddings by Flexible Exploitation of Side Information.
Proceedings of the IJCAI 2007, 2007

2006
Nonlinear Dimensionality Reduction with Side Information.
PhD thesis, 2006

Automatic dimensionality selection from the scree plot via the use of profile likelihood.
Comput. Stat. Data Anal., 2006

Fast Freenet: Improving Freenet Performance by Preferential Partition Routing and File Mesh Propagation.
Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2006), 2006

Subjective Mapping.
Proceedings of the Proceedings, 2006

2005
Subjective Localization with Action Respecting Embedding.
Proceedings of the Robotics Research: Results of the 12th International Symposium, 2005

Learning Subjective Representations for Planning.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Action respecting embedding.
Proceedings of the Machine Learning, 2005

Tangent-Corrected Embedding.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004
Transformation-Invariant Embedding for Image Analysis.
Proceedings of the Computer Vision, 2004

2003
Automatic basis selection techniques for RBF networks.
Neural Networks, 2003

2002
Regularized Greedy Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002


  Loading...