Search Results for author:
Found 18 papers, 4 papers with code
HaVTR: Improving Video-Text Retrieval Through Augmentation Using Large Foundation Models
While recent progress in video-text retrieval has been driven by the exploration of powerful model architectures and training strategies, the representation learning ability of video-text retrieval models is still limited due to low-quality and scarce training data annotations.
SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm
We propose a novel type of Artificial Immune System (AIS): Symbiotic Artificial Immune Systems (SAIS), drawing inspiration from symbiotic relationships in biology.
Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems
The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem with broad real-world applications.
CDIDN: A Registration Model with High Deformation Impedance Capability for Long-Term Tracking of Pulmonary Lesion Dynamics
In this paper, we propose a novel registration model called Cascade-Dilation Inter-Layer Differential Network (CDIDN), which exhibits both high deformation impedance capability (DIC) and accuracy.
PaCaNet: A Study on CycleGAN with Transfer Learning for Diversifying Fused Chinese Painting and Calligraphy
Using one-shot learning to increase the creativity of pre-trained models and diversify the content of the fused images.
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction
In this research, we focus on the impact of selecting two types of GNN hyperparameters, those belonging to graph-related layers and those of task-specific layers, on the performance of GNN for molecular property prediction.
Hyperparameter Optimization
Molecular Property Prediction
+1
A Survey on Physarum Polycephalum Intelligent Foraging Behaviour and Bio-Inspired Applications
In recent years, research on Physarum polycephalum has become more popular after Nakagaki et al. (2000) performed their famous experiment showing that Physarum was able to find the shortest route through a maze.
A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks
In particular, the genetic algorithm (GA) for HPO has been explored, which treats GNNs as a black-box model, of which only the outputs can be observed given a set of hyperparameters.
A Systematic Comparison Study on Hyperparameter Optimisation of Graph Neural Networks for Molecular Property Prediction
In this paper, we conducted a theoretical analysis of common and specific features for two state-of-the-art and popular algorithms for HPO: TPE and CMA-ES, and we compared them with random search (RS), which is used as a baseline.
Hyperparameter Optimization
Molecular Property Prediction
+1
A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks
While in the proposed fast evaluation process, the training will be interrupted at an early stage, the difference of RMSE values between the starting and interrupted epochs will be used as a fast score, which implies the potential of the GNN being considered.
ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network Architectures
In addition, in order to facilitate the mutation operation, we propose a novel two-component based neural structure coding strategy.
Guessing State Tracking for Visual Dialogue
This paper proposes a guessing state for the Guesser, and regards guess as a process with change of guessing state through a dialogue.
Short Text Classification via Term Graph
Short text classi cation is a method for classifying short sentence with prede ned labels.
ImmuNeCS: Neural Committee Search by an Artificial Immune System
Instead of searching for the 1-best architecture for a given task, we focus on building a population of neural networks that are then ensembled into a neural network committee, an approach we dub 'Neural Committee Search'.
Visual Dialogue State Tracking for Question Generation
A visual dialogue state is defined as the distribution on objects in the image as well as representations of objects.
DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence
In this paper we propose DeepSwarm, a novel neural architecture search (NAS) method based on Swarm Intelligence principles.
Towards making NLG a voice for interpretable Machine Learning
This paper presents a study to understand the issues related to using NLG to humanise explanations from a popular interpretable machine learning framework called LIME.
BIG-bench Machine Learning
Interpretable Machine Learning
+1
e-Distance Weighted Support Vector Regression
We propose a novel support vector regression approach called e-Distance Weighted Support Vector Regression (e-DWSVR). e-DWSVR specifically addresses two challenging issues in support vector regression: first, the process of noisy data; second, how to deal with the situation when the distribution of boundary data is different from that of the overall data.
