8 papers
Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles
Mojtaba Moattari
Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and produce human-understandabl…
Precise classification of low quality G-banded Chromosome Images by reliability metrics and data pruning classifier
Mojtaba Moattari
In the last decade, due to high resolution cameras and accurate meta-phase analyzes, the accuracy of chromosome classification has improved substantially. However, current Karyotyp…
Yet Unnoticed in LSTM: Binary Tree Based Input Reordering, Weight Regularization, and Gate Nonlinearization
Mojtaba Moattari
LSTM models used in current Machine Learning literature and applications, has a promising solution for permitting long term information using gating mechanisms that forget and redu…
Beyond Correlation: Learning Supervised, Sample-Distinct, and Eigenimage-Interpretable Representations
Mojtaba Moattari
Conventional dimensionality reduction methods mainly optimize variance or correlation, leaving statistical dependence, data diversity, contrast, and interpretability under addresse…
ProjB: An Improved Bilinear Biased ProjE model for Knowledge Graph Completion
Mojtaba Moattari, Sahar Vahdati, Farhana Zulkernine
Knowledge Graph Embedding (KGE) methods have gained enormous attention from a wide range of AI communities including Natural Language Processing (NLP) for text generation, classifi…
Uncertainty Principle based optimization; new metaheuristics framework
Mojtaba Moattari, Mohammad Hassan Moradi, Emad Roshandel
To more flexibly balance between exploration and exploitation, a new meta-heuristic method based on Uncertainty Principle concepts is proposed in this paper. UP is is proved effect…