6 papers
Obligation-Producing Actions
Kalonji Kalala, Iluju Kiringa, Tet Yeap
This paper proposes a Situation Calculus solution to the frame problem for obligation-producing actions, which are actions that create obligations on the part of the agent that per…
Robust Auto-associative Memory via Convolutional Restricted Hopfield Networks
Ci Lin, Tet Yeap, Iluju Kiringa
Associative memory models play a fundamental role in pattern retrieval, but their performance often degrades under adversarial perturbations and severe input corruptions. Existing…
Preserving Temporal Dynamics in Time Series Generation
Ci Lin, Futong Li, Tet Yeap +1
Time-series data augmentation plays a crucial role in regression-oriented forecasting tasks, where limited data restricts the performance of deep learning models. While Generative…
Robust Bidirectional Associative Memory via Regularization Inspired by the Subspace Rotation Algorithm
Ci Lin, Tet Yeap, Iluju Kiringa +1
Bidirectional Associative Memory (BAM) trained with Bidirectional Backpropagation (B-BP) often suffers from poor robustness and high sensitivity to noise and adversarial attacks. T…
DeepDefense: Robust Learning via Layer-Wise Gradient-Feature Alignment
Ci Lin, Tet Yeap, Iluju Kiringa +1
Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predictions. In this paper, we propos…
Specifying an Obligation Taxonomy in the Non-Markovian Situation Calculus
Kalonji Kalala, Iluju Kiringa, Tet Yeap
Over more than three decades, the Situation Calculus has established itself as an elegant, powerful, and concise formalism for specifying dynamical domains as well as for reasoning…