10 papers
Beyond Neural Networks: Symbolic Reasoning over Wavelet Logic Graph Signals
Andrew Kiruluta, Andreas Lemos, Priscilla Burity
We present a fully non neural learning framework based on Graph Laplacian Wavelet Transforms (GLWT). Unlike traditional architectures that rely on convolutional, recurrent, or atte…
Operator-Based Machine Intelligence: A Hilbert Space Framework for Spectral Learning and Symbolic Reasoning
Andrew Kiruluta, Andreas Lemos, Priscilla Burity
Traditional machine learning models, particularly neural networks, are rooted in finite-dimensional parameter spaces and nonlinear function approximations. This report explores an…
History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM
Andrew Kiruluta, Andreas Lemos, Priscilla Burity
We present CAGSR-vLLM-MTC, an extension of our Self-Supervised Cross-Attention-Guided Reinforcement (CAGSR) framework, now implemented on the high-performance vLLM runtime, to addr…
Hierarchical Attention Diffusion Networks with Object Priors for Video Change Detection
Andrew Kiruluta, Eric Lundy, Andreas Lemos
We present a unified change detection pipeline that combines instance level masking, multi\-scale attention within a denoising diffusion model, and per pixel semantic classificatio…
Beyond Self Attention: A Subquadratic Fourier Wavelet Transformer with Multi Modal Fusion
Andrew Kiruluta, Andreas Lemos, Eric Lundy
We revisit the use of spectral techniques to replaces the attention mechanism in Transformers through Fourier Transform based token mixing, and present a comprehensive and novel re…
Unsupervised Machine Learning Hybrid Approach Integrating Linear Programming in Loss Function: A Robust Optimization Technique
Andrew Kiruluta, Andreas Lemos
This paper presents a novel hybrid approach that integrates linear programming (LP) within the loss function of an unsupervised machine learning model. By leveraging the strengths…