Search Results for author:
Found 43 papers, 7 papers with code
ROG$_{PL}$: Robust Open-Set Graph Learning via Region-Based Prototype Learning
In specific, ROG$_{PL}$ consists of two modules, i. e., denoising via label propagation and open-set prototype learning via regions.
Unsupervised multiple choices question answering via universal corpus
Unsupervised question answering is a promising yet challenging task, which alleviates the burden of building large-scale annotated data in a new domain.
MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property
In this paper, we contribute a new benchmark, the first Multilingual-oriented quiZ on Intellectual Property (MoZIP), for the evaluation of LLMs in the IP domain.
Representation Surgery for Multi-Task Model Merging
That is, there is a significant discrepancy in the representation distribution between the merged and individual models, resulting in poor performance of merged MTL.
Multi-level Cross-modal Alignment for Image Clustering
Recently, the cross-modal pretraining model has been employed to produce meaningful pseudo-labels to supervise the training of an image clustering model.
Phase-Specific Augmented Reality Guidance for Microscopic Cataract Surgery Using Long-Short Spatiotemporal Aggregation Transformer
Phacoemulsification cataract surgery (PCS) is a routine procedure conducted using a surgical microscope, heavily reliant on the skill of the ophthalmologist.
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
For the medical domain, we present a large collection of anatomical shapes (e. g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems.
$\mathcal{G}^2Pxy$: Generative Open-Set Node Classification on Graphs with Proxy Unknowns
Node classification is the task of predicting the labels of unlabeled nodes in a graph.
Apple Vision Pro for Healthcare: "The Ultimate Display"? -- Entering the Wonderland of Precision Medicine
At the Worldwide Developers Conference (WWDC) in June 2023, Apple introduced the Vision Pro.
Practical and General Backdoor Attacks against Vertical Federated Learning
The main challenge of this attack is to allow an attacker without access to the data labels, to perform an effective attack.
A Survey for Efficient Open Domain Question Answering
Thus, a trade-off between accuracy, memory consumption and processing speed is pursued.
Semantic-Enhanced Image Clustering
In this paper, we propose to investigate the task of image clustering with the help of a visual-language pre-training model.
PrUE: Distilling Knowledge from Sparse Teacher Networks
Besides, our method allows researchers to distill knowledge from deeper networks to improve students further.
Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network
Automatic ECG classification methods, especially the deep learning based ones, have been proposed to detect cardiac abnormalities using ECG records, showing good potential to improve clinical diagnosis and help early prevention of cardiovascular diseases.
CLTS+: A New Chinese Long Text Summarization Dataset with Abstractive Summaries
In order to solve this problem, we paraphrase the reference summaries in CLTS, the Chinese Long Text Summarization dataset, correct errors of factual inconsistencies, and propose the first Chinese Long Text Summarization dataset with a high level of abstractiveness, CLTS+, which contains more than 180K article-summary pairs and is available online.
An Inexact Augmented Lagrangian Algorithm for Training Leaky ReLU Neural Network with Group Sparsity
Moreover, we show the relationship between the new model and the original problem.
Deep Unsupervised Hashing with Latent Semantic Components
Firstly, DSCH constructs a semantic component structure by uncovering the fine-grained semantics components of images with a Gaussian Mixture Modal~(GMM), where an image is represented as a mixture of multiple components, and the semantics co-occurrence are exploited.
DEFEAT: Deep Hidden Feature Backdoor Attacks by Imperceptible Perturbation and Latent Representation Constraints
Backdoor attack is a type of serious security threat to deep learning models. An adversary can provide users with a model trained on poisoned data to manipulate prediction behavior in test stage using a backdoor.
Deep Self-Adaptive Hashing for Image Retrieval
Secondly, we measure the priorities of data pairs with PIC and assign adaptive weights to them, which is relies on the assumption that more dissimilar data pairs contain more discriminative information for hash learning.
A Riemannian smoothing steepest descent method for non-Lipschitz optimization on submanifolds
In this paper, we propose a Riemannian smoothing steepest descent method to minimize a nonconvex and non-Lipschitz function on submanifolds.
Pure Characteristics Demand Models and Distributionally Robust Mathematical Programs with Stochastic Complementarity Constraints
We formulate pure characteristics demand models under uncertainties of probability distributions as distributionally robust mathematical programs with stochastic complementarity constraints (DRMP-SCC).
Optimization and Control 90C15, 90C33, 90C26
A Distributed Training Algorithm of Generative Adversarial Networks with Quantized Gradients
In this paper, we propose a {distributed GANs training algorithm with quantized gradient, dubbed DQGAN,} which is the first distributed training method with quantized gradient for GANs.
A weakly supervised registration-based framework for prostate segmentation via the combination of statistical shape model and CNN
To address this problem, we proposed a weakly supervised registration-based framework for the precise prostate segmentation, by combining convolutional neural network (CNN) with statistical shape model (SSM).
Incorporating Uncertain Segmentation Information into Chinese NER for Social Media Text
Chinese word segmentation is necessary to provide word-level information for Chinese named entity recognition (NER) systems.
Chinese Named Entity Recognition
Chinese Word Segmentation
+6
Leveraging Long and Short-Term Information in Content-Aware Movie Recommendation via Adversarial Training
Movie recommendation systems provide users with ranked lists of movies based on individual’s preferences and constraints.
Improving Abstractive Text Summarization with History Aggregation
Recent neural sequence to sequence models have provided feasible solutions for abstractive summarization.
Sparse Solutions of a Class of Constrained Optimization Problems
Specifically, without any condition on the matrix $A$, we provide upper bounds in cardinality and infinity norm for the optimal solutions, and show that all optimal solutions must be on the boundary of the feasible set when $0<p<1$.
Triple Trustworthiness Measurement for Knowledge Graph
The Knowledge graph (KG) uses the triples to describe the facts in the real world.
Clinical evaluation of semi-automatic opensource algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action
Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice.
In-depth Assessment of an Interactive Graph-based Approach for the Segmentation for Pancreatic Metastasis in Ultrasound Acquisitions of the Liver with two Specialists in Internal Medicine
Ultimately, the algorithm enables a fast and accurate segmentation of liver metastasis in clinical US images, which can support the manual outlining in daily practice.
Vertebral body segmentation with GrowCut: Initial experience, workflow and practical application
In this contribution, we used the GrowCut segmentation algorithm publicly available in three-dimensional Slicer for three-dimensional segmentation of vertebral bodies.
A Self-Balanced Min-Cut Algorithm for Image Clustering
In the new method, a self-balanced min-cut model is proposed in which the Exclusive Lasso is implicitly introduced as a balance regularizer in order to produce balanced partition.
Identifying and Tracking Sentiments and Topics from Social Media Texts during Natural Disasters
We study the problem of identifying the topics and sentiments and tracking their shifts from social media texts in different geographical regions during emergencies and disasters.
Computer-aided position planning of miniplates to treat facial bone defects
In this contribution, a software system for computer-aided position planning of miniplates to treat facial bone defects is proposed.
Computer-aided implant design for the restoration of cranial defects
Patient-specific cranial implants are important and necessary in the surgery of cranial defect restoration.
A Non-monotone Alternating Updating Method for A Class of Matrix Factorization Problems
Finally, we conduct some numerical experiments using real datasets to compare our method with some existing efficient methods for non-negative matrix factorization and matrix completion.
Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images
In this contribution, we present the results of an interactive segmentation approach for liver metastases in US acquisitions.
US-Cut: Interactive Algorithm for rapid Detection and Segmentation of Liver Tumors in Ultrasound Acquisitions
We present an interactive segmentation approach for liver tumors in US acquisitions.
A semi-automatic computer-aided method for surgical template design
Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface.
Linear Convergence of Proximal Gradient Algorithm with Extrapolation for a Class of Nonconvex Nonsmooth Minimization Problems
In this paper, we study the proximal gradient algorithm with extrapolation for minimizing the sum of a Lipschitz differentiable function and a proper closed convex function.
Generalized Conjugate Gradient Methods for $\ell_1$ Regularized Convex Quadratic Programming with Finite Convergence
In this paper we propose some generalized CG (GCG) methods for solving the $\ell_1$-regularized (possibly not strongly) convex QP that terminate at an optimal solution in a finite number of iterations.
Interactive Volumetry Of Liver Ablation Zones
The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.
Penalty methods for a class of non-Lipschitz optimization problems
We consider a class of constrained optimization problems with a possibly nonconvex non-Lipschitz objective and a convex feasible set being the intersection of a polyhedron and a possibly degenerate ellipsoid.
