58 citations · 61 across the 10 of their papers we have counts for
10 papers
A Vector Symbolic Approach to Multiple Instance Learning
Ehsan Ahmed Dhrubo, Mohammad Mahmudul Alam, Edward Raff +2
Multiple Instance Learning (MIL) tasks impose a strict logical constraint: a bag is labeled positive if and only if at least one instance within it is positive. While this iff cons…
A Walsh Hadamard Derived Linear Vector Symbolic Architecture
Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff +3
Vector Symbolic Architectures (VSAs) are one approach to developing Neuro-symbolic AI, where two vectors in are `bound' together to produce a new vector in the same…
Automated Virtual Product Placement and Assessment in Images using Diffusion Models
Mohammad Mahmudul Alam, Negin Sokhandan, Emmett Goodman
In Virtual Product Placement (VPP) applications, the discrete integration of specific brand products into images or videos has emerged as a challenging yet important task. This pap…
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection
Mohammad Mahmudul Alam, Edward Raff, Stella Biderman +2
Malware detection is an interesting and valuable domain to work in because it has significant real-world impact and unique machine-learning challenges. We investigate existing long…
Towards Generalization in Subitizing with Neuro-Symbolic Loss using Holographic Reduced Representations
Mohammad Mahmudul Alam, Edward Raff, Tim Oates
While deep learning has enjoyed significant success in computer vision tasks over the past decade, many shortcomings still exist from a Cognitive Science (CogSci) perspective. In p…
DDxT: Deep Generative Transformer Models for Differential Diagnosis
Mohammad Mahmudul Alam, Edward Raff, Tim Oates +1
Differential Diagnosis (DDx) is the process of identifying the most likely medical condition among the possible pathologies through the process of elimination based on evidence. An…
Recasting Self-Attention with Holographic Reduced Representations
Mohammad Mahmudul Alam, Edward Raff, Stella Biderman +2
In recent years, self-attention has become the dominant paradigm for sequence modeling in a variety of domains. However, in domains with very long sequence lengths the $\mathcal{O}…
Lempel-Ziv Networks
Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz +3
Sequence processing has long been a central area of machine learning research. Recurrent neural nets have been successful in processing sequences for a number of tasks; however, th…
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations
Mohammad Mahmudul Alam, Edward Raff, Tim Oates +1
Due to the computational cost of running inference for a neural network, the need to deploy the inferential steps on a third party's compute environment or hardware is common. If t…
Unified Learning Approach for Egocentric Hand Gesture Recognition and Fingertip Detection
Mohammad Mahmudul Alam, Mohammad Tariqul Islam, S. M. Mahbubur Rahman
Head-mounted device-based human-computer interaction often requires egocentric recognition of hand gestures and fingertips detection. In this paper, a unified approach of egocentri…