Blog
Gradient-Optimized Fuzzy Classifier: A Benchmark Study Against State-of-the-Art Models
This paper presents a performance benchmarking study of a Gradient-Optimized Fuzzy Inference System (GF) classifier against several state-of-the-art machine learning models, including Random Forest, XGBoost, Logistic Regression, Support Vector Machines, and Neural Networks. The evaluation was conducted across five datasets from the...
Term Coding for Extremal Combinatorics: Dispersion and Complexity Dichotomies
We introduce \emph{Term Coding}, a novel framework for analysing extremal problems in discrete mathematics by encoding them as finite systems of \emph{term equations} (and, optionally, \emph{non-equality constraints}). In its basic form, all variables range over a single domain, and we seek an...
Boosting Classifier Performance with Opposition-Based Data Transformation
In this paper, we introduce a novel data transformation framework based on Opposition-Based Learning (OBL) to boost the performance of traditional classification algorithms. Originally developed to accelerate convergence in optimization tasks, OBL is leveraged here to generate synthetic opposite samples that replace...
A Geometric Approach to Problems in Optimization and Data Science
We give new results for problems in computational and statistical machine learning using tools from high-dimensional geometry and probability. We break up our treatment into two parts. In Part I, we focus on computational considerations in optimization. Specifically, we give new algorithms...
Shape Alignment via Allen-Cahn Nonlinear-Convection
This paper demonstrates the impact of a phase field method on shape registration to align shapes of possibly different topology. It yields new insights into the building of discrepancy measures between shapes regardless of topology, which would have applications in fields of...
Affect Models Have Weak Generalizability to Atypical Speech
Speech and voice conditions can alter the acoustic properties of speech, which could impact the performance of paralinguistic models for affect for people with atypical speech. We evaluate publicly available models for recognizing categorical and dimensional affect from speech on a dataset...
Linear Time Subsequence and Supersequence Regex Matching
It is well-known that checking whether a given string $w$ matches a given regular expression $r$ can be done in quadratic time $O(|w|\cdot |r|)$ and that this cannot be improved to a truly subquadratic running time of $O((|w|\cdot |r|)^{1-\epsilon})$ assuming the strong...
Deep, data-driven modeling of room acoustics: literature review and research perspectives
Our everyday auditory experience is shaped by the acoustics of the indoor environments in which we live. Room acoustics modeling is aimed at establishing mathematical representations of acoustic wave propagation in such environments. These representations are relevant to a variety of problems...
GENCNIPPET: Automated Generation of Code Snippets for Supporting Programming Questions
Context: Software developers often ask questions on Technical Q&A forums like Stack Overflow (SO) to seek solutions to their programming-related problems (e.g., errors and unexpected behavior of code). Problem: Many questions miss required code snippets due to the lack of readily available...
CHIME All-sky Multiday Pulsar Stacking Search (CHAMPSS): System Overview and First Discoveries
We describe the CHIME All-sky Multiday Pulsar Stacking Search (CHAMPSS) project. This novel radio pulsar survey revisits the full Northern Sky daily, offering unprecedented opportunity to detect highly intermittent pulsars, as well as faint sources via long-term data stacking. CHAMPSS uses the...