18 citations · 28 across the 44 of their papers we have counts for
8 papers · 1 filter
Root Cause Explanation of Outliers under Noisy Mechanisms
Phuoc Nguyen, Truyen Tran, Sunil Gupta +2
Identifying root causes of anomalies in causal processes is vital across disciplines. Once identified, one can isolate the root causes and implement necessary measures to restore t…
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection
Tuan Hoang, Santu Rana, Sunil Gupta +1
Recent data-privacy laws have sparked interest in machine unlearning, which involves removing the effect of specific training samples from a learnt model as if they were never pres…
LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying
Thommen George Karimpanal, Laknath Buddhika Semage, Santu Rana +4
Large language models (LLMs) have recently demonstrated their impressive ability to provide context-aware responses via text. This ability could potentially be used to predict plau…
Beyond Surprise: Improving Exploration Through Surprise Novelty
Hung Le, Kien Do, Dung Nguyen +1
We present a new computing model for intrinsic rewards in reinforcement learning that addresses the limitations of existing surprise-driven explorations. The reward is the novelty…
Predictive Modeling through Hyper-Bayesian Optimization
Manisha Senadeera, Santu Rana, Sunil Gupta +1
Model selection is an integral problem of model based optimization techniques such as Bayesian optimization (BO). Current approaches often treat model selection as an estimation pr…
BO-Muse: A human expert and AI teaming framework for accelerated experimental design
Sunil Gupta, Alistair Shilton, Arun Kumar A +7
In this paper we introduce BO-Muse, a new approach to human-AI teaming for the optimization of expensive black-box functions. Inspired by the intrinsic difficulty of extracting exp…
Zero-shot Sim2Real Adaptation Across Environments
Buddhika Laknath Semage, Thommen George Karimpanal, Santu Rana +1
Simulation based learning often provides a cost-efficient recourse to reinforcement learning applications in robotics. However, simulators are generally incapable of accurately rep…
Memory-Augmented Theory of Mind Network
Dung Nguyen, Phuoc Nguyen, Hung Le +3
Social reasoning necessitates the capacity of theory of mind (ToM), the ability to contextualise and attribute mental states to others without having access to their internal cogni…