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Found 32 papers, 9 papers with code
Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation
As opposed to manual feature engineering which is tedious and difficult to scale, network representation learning has attracted a surge of research interests as it automates the process of feature learning on graphs.
Editing Text in the Wild
Specifically, we propose an end-to-end trainable style retention network (SRNet) that consists of three modules: text conversion module, background inpainting module and fusion module.
Ranked #1 on
Image Inpainting
on StreetView
Collaborative Large Language Model for Recommender Systems
We first extend the vocabulary of pretrained LLMs with user/item ID tokens to faithfully model user/item collaborative and content semantics.
GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
This synergy equips LLMs with the ability to proficiently interpret and reason on graph data, harnessing the superior expressive power of graph learning models.
Path-Specific Counterfactual Fairness for Recommender Systems
But since sensitive features may also affect user interests in a fair manner (e. g., race on culture-based preferences), indiscriminately eliminating all the influences of sensitive features inevitably degenerate the recommendations quality and necessary diversities.
LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations
Additionally, we introduce graph relationship understanding and analysis functions into LLMs to enhance their focus on connectivity information in graph data.
Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation
We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost.
Integrating Holistic and Local Information to Estimate Emotional Reaction Intensity
We handle variable video length with a regression token that accumulates information from all frames into a fixed-dimensional vector independent of video length.
SlangSD: Building and Using a Sentiment Dictionary of Slang Words for Short-Text Sentiment Classification
To this end, we propose to build the first sentiment dictionary of slang words to aid sentiment analysis of social media content.
Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval
Specifically, this method can capture both the inherent information in the source codes and the semantic information hidden in the comments, descriptions, and identifiers of the source codes.
Capturing Evolution Genes for Time Series Data
The modeling of time series is becoming increasingly critical in a wide variety of applications.
Data-Rate Driven Transmission Strategy for Deep Learning Based Communication Systems
The GDR scheme can achieve higher data rate than the conventional one-hot vector scheme with comparable BLER performance.
Information Theory Information Theory
Fine-grained Generalization Analysis of Vector-valued Learning
In this paper, we initiate the generalization analysis of regularized vector-valued learning algorithms by presenting bounds with a mild dependency on the output dimension and a fast rate on the sample size.
Extreme Multi-Label Classification
General Classification
+2
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition
Iterative distillation over multiple generations significantly improves performance in both emotion recognition and uncertainty estimation.
Stability and Generalization for Randomized Coordinate Descent
Randomized coordinate descent (RCD) is a popular optimization algorithm with wide applications in solving various machine learning problems, which motivates a lot of theoretical analysis on its convergence behavior.
A Novel Two-stage Design Scheme of Equalizers for Uplink FBMC/OQAM-based Massive MIMO Systems
However, existing works show that there remains residual interference after single-tap equalization even with infinite number of BS antennas, leading to a limitation of achievable signal-to-interference-plus-noise ratio (SINR) performance.
Fast and Arbitrary Beam Pattern Design for RIS-Assisted Terahertz Wireless Communication
Reconfigurable intelligent surface (RIS) can assist terahertz wireless communication to restore the fragile line-of-sight links and facilitate beam steering.
MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining
Specifically, we transform text data into synthesized text images to unify the data modalities of vision and language, and enhance the language modeling capability of the sequence decoder using a proposed masked image-language modeling scheme.
Equivalence of SS-based MPC and ARX-based MPC
Two kinds of control-oriented models used in MPC are the state-space (SS) model and the input-output model (such as the ARX model).
A rapid-prototype MPC tool based on gPROMS platform
The gPROMS-MPC tool implements our previous construction-free CDAL and the online parametric active-set qpOASES algorithms to solve sparse or condensed MPC problem formulations, respectively, for possible successive linearization or high state-dimension cases.
An interpretative and adaptive MPC for nonlinear systems
This interpretative ARX model is then updated online by the EKF algorithm, which is modified as a decoupled one without matrix-inverse operator.
Remote Work Optimization with Robust Multi-channel Graph Neural Networks
Introducing a brand new workplace type naturally leads to the cold-start problem, which is particularly more common for less active job seekers.
RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid
In comparison to optical flow, phase provides more localized motion estimates, which are essential for ME spotting, resulting in higher performance.
A direct optimization algorithm for input-constrained MPC
Providing an execution time certificate is a pressing requirement when deploying Model Predictive Control (MPC) in real-time embedded systems such as microcontrollers.
Hybrid Control Policy for Artificial Pancreas via Ensemble Deep Reinforcement Learning
Objective: The artificial pancreas (AP) has shown promising potential in achieving closed-loop glucose control for individuals with type 1 diabetes mellitus (T1DM).
Channel Modeling for Heterogeneous Vehicular ISAC System with Shared Clusters
In this paper, we consider the channel modeling of a heterogeneous vehicular integrated sensing and communication (ISAC) system, where a dual-functional multi-antenna base station (BS) intends to communicate with a multi-antenna vehicular receiver (MR) and sense the surrounding environments simultaneously.
AI-driven emergence of frequency information non-uniform distribution via THz metasurface spectrum prediction
Recently, artificial intelligence has been extensively deployed across various scientific disciplines, optimizing and guiding the progression of experiments through the integration of abundant datasets, whilst continuously probing the vast theoretical space encapsulated within the data.
Large Scale Foundation Models for Intelligent Manufacturing Applications: A Survey
Although the applications of artificial intelligence especially deep learning had greatly improved various aspects of intelligent manufacturing, they still face challenges for wide employment due to the poor generalization ability, difficulties to establish high-quality training datasets, and unsatisfactory performance of deep learning methods.
LinkSAGE: Optimizing Job Matching Using Graph Neural Networks
This methodology decouples the training of the GNN model from that of existing Deep Neural Nets (DNN) models, eliminating the need for frequent GNN retraining while maintaining up-to-date graph signals in near realtime, allowing for the effective integration of GNN insights through transfer learning.
An Execution-time-certified Riccati-based IPM Algorithm for RTI-based Input-constrained NMPC
The execution-time certified capability of the algorithm is theoretically and numerically validated through a case study involving nonlinear control of the chaotic Lorenz system.
Leveraging Foundation Model Automatic Data Augmentation Strategies and Skeletal Points for Hands Action Recognition in Industrial Assembly Lines
We proposed a method of converting hand action recognition problems into hand skeletal trajectory classification problems, which solved the real-time performance problem of industrial algorithms.
An Execution-time-certified QP Algorithm for $\ell_1$ penalty-based Soft-constrained MPC
Providing an execution time certificate and handling possible infeasibility in closed-loop are two pressing requirements of Model Predictive Control (MPC).
