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08/27/2023
Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization
Real-time solutions to the influence blocking maximization (IBM) problem...
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08/18/2023
Meta-learning enhanced next POI recommendation by leveraging check-ins from auxiliary cities
Most existing point-of-interest (POI) recommenders aim to capture user p...
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06/26/2023
Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications
The multiple-choice knapsack problem (MCKP) is a classic NP-hard combina...
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06/14/2023
Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects
Conversational recommender systems (CRSs) have become crucial emerging r...
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05/24/2023
Prompt Evolution for Generative AI: A Classifier-Guided Approach
Synthesis of digital artifacts conditioned on user prompts has become an...
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04/26/2023
Bayesian Federated Learning: A Survey
Federated learning (FL) demonstrates its advantages in integrating distr...
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04/05/2023
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search
Approximate nearest neighbour (ANN) search is an essential component of ...
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02/28/2023
Policy Dispersion in Non-Markovian Environment
Markov Decision Process (MDP) presents a mathematical framework to formu...
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02/03/2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry
We present a novel loss formulation for efficient learning of complex dy...
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12/15/2022
Neuroevolution Surpasses Stochastic Gradient Descent for Physics-Informed Neural Networks
The potential of learned models for fundamental scientific research and ...
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10/14/2022
Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learning
Graph attention networks (GATs) are powerful tools for analyzing graph d...
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09/01/2022
A Multi-Channel Next POI Recommendation Framework with Multi-Granularity Check-in Signals
Current study on next POI recommendation mainly explores user sequential...
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08/29/2022
Understanding Diversity in Session-Based Recommendation
Current session-based recommender systems (SBRSs) mainly focus on maximi...
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06/22/2022
DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
Recently, one critical issue looms large in the field of recommender sys...
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06/15/2022
Masked Frequency Modeling for Self-Supervised Visual Pre-Training
We present Masked Frequency Modeling (MFM), a unified frequency-domain-b...
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05/31/2022
Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction
Recently, neural implicit surfaces learning by volume rendering has beco...
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05/19/2022
Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data
Granger causality is a commonly used method for uncovering information f...
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05/09/2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
Model robustness is vital for the reliable deployment of machine learnin...
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05/08/2022
A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
Artificial Intelligence (AI) is a fast-growing research and development ...
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05/02/2022
Jack and Masters of All Trades: One-Pass Learning of a Set of Model Sets from Foundation AI Models
For deep learning, size is power. Massive neural nets trained on broad d...
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03/21/2022
Lean Evolutionary Reinforcement Learning by Multitasking with Importance Sampling
Studies have shown evolution strategies (ES) to be a promising approach ...
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02/25/2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains
Multi-task Gaussian process (MTGP) is a well-known non-parametric Bayesi...
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10/29/2021
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method
In this study, novel physics-informed neural network (PINN) methods for ...
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09/27/2021
Half a Dozen Real-World Applications of Evolutionary Multitasking and More
Until recently, the potential to transfer evolved skills across distinct...
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09/20/2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
A physics-informed neural network (PINN) uses physics-augmented loss fun...
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07/31/2021
Word2Pix: Word to Pixel Cross Attention Transformer in Visual Grounding
Current one-stage methods for visual grounding encode the language query...
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06/22/2021
Unsupervised Object-Level Representation Learning from Scene Images
Contrastive self-supervised learning has largely narrowed the gap to sup...
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04/14/2021
Multi-Party Dual Learning
The performance of machine learning algorithms heavily relies on the ava...
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03/07/2021
RNA Alternative Splicing Prediction with Discrete Compositional Energy Network
A single gene can encode for different protein versions through a proces...
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02/23/2021
Multi-Space Evolutionary Search for Large-Scale Optimization
In recent years, to improve the evolutionary algorithms used to solve op...
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02/05/2021
Graph Joint Attention Networks
Graph attention networks (GATs) have been recognized as powerful tools f...
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01/06/2021
Can Transfer Neuroevolution Tractably Solve Your Differential Equations?
This paper introduces neuroevolution for solving differential equations....
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12/03/2020
Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances
In today's digital world, we are confronted with an explosion of data an...
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10/06/2020
Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder
This paper demonstrates a fatal vulnerability in natural language infere...
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08/29/2020
Modulating Scalable Gaussian Processes for Expressive Statistical Learning
For a learning task, Gaussian process (GP) is interested in learning the...
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08/26/2020
Delving into Inter-Image Invariance for Unsupervised Visual Representations
Contrastive learning has recently shown immense potential in unsupervise...
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08/14/2020
Defending Adversarial Attacks without Adversarial Attacks in Deep Reinforcement Learning
Many recent studies in deep reinforcement learning (DRL) have proposed t...
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06/18/2020
Online Deep Clustering for Unsupervised Representation Learning
Joint clustering and feature learning methods have shown remarkable perf...
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06/05/2020
CoCon: A Self-Supervised Approach for Controlled Text Generation
Pretrained Transformer-based language models (LMs) display remarkable na...
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05/18/2020
Deep Latent-Variable Kernel Learning
Deep kernel learning (DKL) leverages the connection between Gaussian pro...
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04/28/2020
Heterogeneous Representation Learning: A Review
The real-world data usually exhibits heterogeneous properties such as mo...
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12/21/2019
Jacobian Adversarially Regularized Networks for Robustness
Adversarial examples are crafted with imperceptible perturbations with t...
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12/11/2019
What it Thinks is Important is Important: Robustness Transfers through Input Gradients
Adversarial perturbations are imperceptible changes to input pixels that...
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11/19/2019
Poison as a Cure: Detecting Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
Deep learning models have recently shown to be vulnerable to backdoor po...
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11/18/2019
A Multi-Task Gradient Descent Method for Multi-Label Learning
Multi-label learning studies the problem where an instance is associated...
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11/10/2019
Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy
Recent studies have revealed that neural network-based policies can be e...
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10/08/2019
DEVDAN: Deep Evolving Denoising Autoencoder
The Denoising Autoencoder (DAE) enhances the flexibility of the data str...
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10/08/2019
Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
Autonomous construction of deep neural network (DNNs) is desired for dat...
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09/14/2019
Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods
Gaussian process classification (GPC) provides a flexible and powerful s...
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01/02/2019