Search Results for author:
Found 32 papers, 9 papers with code
Adapprox: Adaptive Approximation in Adam Optimization via Randomized Low-Rank Matrices
As deep learning models exponentially increase in size, optimizers such as Adam encounter significant memory consumption challenges due to the storage of first and second moment data.
Caching-Augmented Lifelong Multi-Agent Path Finding
In this paper, we present a novel mechanism named Caching-Augmented Lifelong MAPF (CAL-MAPF), designed to improve the performance of Lifelong MAPF.
A General and Flexible Multi-concept Parsing Framework for Multilingual Semantic Matching
Although DC-Match is a simple yet effective method for semantic matching, it highly depends on the external NER techniques to identify the keywords of sentences, which limits the performance of semantic matching for minor languages since satisfactory NER tools are usually hard to obtain.
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation.
Agents meet OKR: An Object and Key Results Driven Agent System with Hierarchical Self-Collaboration and Self-Evaluation
In this study, we introduce the concept of OKR-Agent designed to enhance the capabilities of Large Language Models (LLMs) in task-solving.
HEProto: A Hierarchical Enhancing ProtoNet based on Multi-Task Learning for Few-shot Named Entity Recognition
Great efforts have been made on this task with competitive performance, however, they usually treat the two subtasks, namely span detection and type classification, as mutually independent, and the integrity and correlation between subtasks have been largely ignored.
Ranked #3 on
Few-shot NER
on Few-NERD (INTER)
AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing
Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP).
Differentiable modeling to unify machine learning and physical models and advance Geosciences
Here we present differentiable geoscientific modeling as a powerful pathway toward dissolving the perceived barrier between them and ushering in a paradigm shift.
ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks
Causal chain reasoning (CCR) is an essential ability for many decision-making AI systems, which requires the model to build reliable causal chains by connecting causal pairs.
Recognition and Prediction of Surgical Gestures and Trajectories Using Transformer Models in Robot-Assisted Surgery
In this paper, we propose the novel use of a Transformer model for three tasks: gesture recognition, gesture prediction, and trajectory prediction during RAS.
A Random Forest and Current Fault Texture Feature-Based Method for Current Sensor Fault Diagnosis in Three-Phase PWM VSR
The current sensor faults may bring hidden danger or damage to the whole system; therefore, this paper proposed a random forest (RF) and current fault texture feature-based method for current sensor fault diagnosis in three-phase PWM VSR systems.
Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes
Specifically, low-frequency eigenmodes, which are considered sufficient to capture the essence of the functional network, contribute little to functional connectivity reconstruction in transmodal regions, resulting in structure-function decoupling along the unimodal-transmodal gradient.
A graph-transformer for whole slide image classification
Here we present a Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images, called GTP, to predict disease grade.
Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition
Recent years have witnessed the improving performance of Chinese Named Entity Recognition (NER) from proposing new frameworks or incorporating word lexicons.
Chinese Named Entity Recognition
named-entity-recognition
+3
Multi-Level Attention for Unsupervised Person Re-Identification
The attention mechanism is widely used in deep learning because of its excellent performance in neural networks without introducing additional information.
TCMPR: TCM Prescription recommendation based on subnetwork term mapping and deep learning
In addition, the comprehensive experiments of TCMPR with different hyper parameters (i. e., feature embedding, feature dimension and feature fusion) that demonstrates that our method has high performance on TCM prescription recommendation and potentially promote clinical diagnosis and treatment of TCM precision medicine.
Implicit Neural Deformation for Sparse-View Face Reconstruction
In this work, we present a new method for 3D face reconstruction from sparse-view RGB images.
Scene Synthesis via Uncertainty-Driven Attribute Synchronization
This task is challenging because 3D scenes exhibit diverse patterns, ranging from continuous ones, such as object sizes and the relative poses between pairs of shapes, to discrete patterns, such as occurrence and co-occurrence of objects with symmetrical relationships.
A Game-Theoretic Taxonomy of Visual Concepts in DNNs
In this paper, we rethink how a DNN encodes visual concepts of different complexities from a new perspective, i. e. the game-theoretic multi-order interactions between pixels in an image.
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World
However, the coordination of hundreds of agents in a real-life setting like a railway network remains challenging and the Flatland environment used for the competition models these real-world properties in a simplified manner.
Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis
Clinical diagnosis, which aims to assign diagnosis codes for a patient based on the clinical note, plays an essential role in clinical decision-making.
Summarising Historical Text in Modern Languages
We introduce the task of historical text summarisation, where documents in historical forms of a language are summarised in the corresponding modern language.
A General 3D Non-Stationary Massive MIMO GBSM for 6G Communication Systems
A general three-dimensional (3D) non-stationary massive multiple-input multiple-output (MIMO) geometry-based stochastic model (GBSM) for the sixth generation (6G) communication systems is proposed in the paper.
Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-Identification
To tackle the problem, we propose an online pseudo label generation by hierarchical cluster dynamics for adaptive ReID.
Homophone-based Label Smoothing in End-to-End Automatic Speech Recognition
A new label smoothing method that makes use of prior knowledge of a language at human level, homophone, is proposed in this paper for automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A method for detecting text of arbitrary shapes in natural scenes that improves text spotting
Our text spotting framework, called UHTA, combines UHT with the state-of-the-art text recognition system ASTER.
Ranked #11 on
Scene Text Detection
on Total-Text
Scraping Social Media Photos Posted in Kenya and Elsewhere to Detect and Analyze Food Types
We also propose a scrape-by-keywords methodology and used it to scrape ~30, 000 images and their captions of 38 Kenyan food types.
Deep Neural Network for Semantic-based Text Recognition in Images
A text-recognition network interprets isolated words.
Cartoon Face Recognition: A Benchmark Dataset
Recent years have witnessed increasing attention in cartoon media, powered by the strong demands of industrial applications.
Unsupervised Classification of Street Architectures Based on InfoGAN
Furthermore, we draw a series of heuristic conclusions from the intrinsic information hidden in true images.
iQIYI-VID: A Large Dataset for Multi-modal Person Identification
Multi-modal person identification is a more promising way that we can jointly utilize face, head, body, audio features, and so on.
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
In this paper we develop a new framework that captures the common landscape underlying the common non-convex low-rank matrix problems including matrix sensing, matrix completion and robust PCA.
