Search Results for author:
Found 54 papers, 29 papers with code
Toward Detecting Violations of Differential Privacy
The widespread acceptance of differential privacy has led to the publication of many sophisticated algorithms for protecting privacy.
Cryptography and Security
A Distributed Synchronous SGD Algorithm with Global Top-$k$ Sparsification for Low Bandwidth Networks
Current methods that use AllGather to accumulate the sparse gradients have a communication complexity of $O(kP)$, where $P$ is the number of workers, which is inefficient on low bandwidth networks with a large number of workers.
Proving Differential Privacy with Shadow Execution
Sometimes, combining those two requires substantial changes to program logics: one recent paper is able to verify Report Noisy Max automatically, but it involves a complex verification system using customized program logics and verifiers.
Programming Languages D.2.4
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms
We show that it can also release for free the noisy gap between the approximate maximizer and runner-up.
Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training
Different from the existing end-to-end benchmarks which only present the training time, We try to investigate the impact of hardware, vendor's software library, and deep learning framework on the performance and energy consumption of AI training.
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models
Our results show that object detection can help improve the accuracy of some skin disease classes.
A Survey of Deep Learning Techniques for Neural Machine Translation
In recent years, natural language processing (NLP) has got great development with deep learning techniques.
ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
Then a novel Local Orthogonal Texture-aware Module (LOTM) models the local texture information of proposal features in two orthogonal directions and represents text region with a set of contour points.
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples
We propose CheckDP, the first automated and integrated approach for proving or disproving claims that a mechanism is differentially private.
Programming Languages D.3.1
Optimizing Fitness-For-Use of Differentially Private Linear Queries
In practice, differentially private data releases are designed to support a variety of applications.
Databases
Multi-scale Information Assembly for Image Matting
Image matting is a long-standing problem in computer graphics and vision, mostly identified as the accurate estimation of the foreground in input images.
Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition
Additionally, based on the ensemble of iterative predictions, we propose a self-training method which can learn from unlabeled images effectively.
A Two-Stage Attentive Network for Single Image Super-Resolution
Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and contribute remarkable progress.
A Survey of Transformers
X-formers) have been proposed, however, a systematic and comprehensive literature review on these Transformer variants is still missing.
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track
In this technical report, we present our solution of KDD Cup 2021 OGB Large-Scale Challenge - PCQM4M-LSC Track.
PERT: A Progressively Region-based Network for Scene Text Removal
However, there exists two problems: 1) the implicit erasure guidance causes the excessive erasure to non-text areas; 2) the one-stage erasure lacks the exhaustive removal of text region.
Monocular Visual Analysis for Electronic Line Calling of Tennis Games
We propose a monocular vision technology based ELC method.
Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking
Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking.
From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network
Such operation guides the vision model to use not only the visual texture of characters, but also the linguistic information in visual context for recognition when the visual cues are confused (e. g. occlusion, noise, etc.).
CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation
Acquiring the most representative examples via active learning (AL) can benefit many data-dependent computer vision tasks by minimizing efforts of image-level or pixel-wise annotations.
Switch as a Verifier: Toward Scalable Data Plane Checking via Distributed, On-Device Verification
Data plane verification (DPV) is important for finding network errors.
What Dense Graph Do You Need for Self-Attention?
Transformers have made progress in miscellaneous tasks, but suffer from quadratic computational and memory complexities.
Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs
To avoid retraining an entire model on the whole KGs whenever new entities and triples come, we present a continual alignment method for this task.
Relay Hindsight Experience Replay: Self-Guided Continual Reinforcement Learning for Sequential Object Manipulation Tasks with Sparse Rewards
To solve these tasks efficiently, we propose a novel self-guided continual RL framework, RelayHER (RHER).
Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities
We propose a walk-based inductive reasoning model to tackle the new setting.
Progressive Glass Segmentation
First, we attempt to bridge the characteristic gap between different levels of features by developing a Discriminability Enhancement (DE) module which enables level-specific features to be a more discriminative representation, alleviating the features incompatibility for fusion.
The Open-World Lottery Ticket Hypothesis for OOD Intent Classification
Most existing methods of Out-of-Domain (OOD) intent classification rely on extensive auxiliary OOD corpora or specific training paradigms.
Wider and Higher: Intensive Integration and Global Foreground Perception for Image Matting
This paper reviews recent deep-learning-based matting research and conceives our wider and higher motivation for image matting.
Hierarchical and Progressive Image Matting
In this paper, we propose an end-to-end Hierarchical and Progressive Attention Matting Network (HAttMatting++), which can better predict the opacity of the foreground from single RGB images without additional input.
Discovering New Intents Using Latent Variables
In this paper, starting from the intuition that discovering intents could be beneficial to the identification of the known intents, we propose a probabilistic framework for discovering intents where intent assignments are treated as latent variables.
ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spotting
In this paper, we argue that the limited capacity of language models comes from 1) implicit language modeling; 2) unidirectional feature representation; and 3) language model with noise input.
Ranked #4 on
Text Spotting
on SCUT-CTW1500
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
One-shot neural architecture search (NAS) substantially improves the search efficiency by training one supernet to estimate the performance of every possible child architecture (i. e., subnet).
Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs
We consider knowledge transfer and retention of the learning on growing snapshots of a KG without having to learn embeddings from scratch.
Exploring Stroke-Level Modifications for Scene Text Editing
Moreover, two new datasets (Tamper-Syn2k and Tamper-Scene) are proposed to fill the blank of public evaluation datasets.
Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Survey
Storytelling and narrative are fundamental to human experience, intertwined with our social and cultural engagement.
Rethinking Label Smoothing on Multi-hop Question Answering
Multi-Hop Question Answering (MHQA) is a significant area in question answering, requiring multiple reasoning components, including document retrieval, supporting sentence prediction, and answer span extraction.
GAR: Generalized Autoregression for Multi-Fidelity Fusion
In many scientific research and engineering applications where repeated simulations of complex systems are conducted, a surrogate is commonly adopted to quickly estimate the whole system.
OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases.
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
It improves the training efficiency, remarkably relaxes the requirements on the hardware, and supports efficient large-scale FL experiments with stateful clients by: (1) sequential training clients on devices; (2) decomposing original aggregation into local and global aggregation on devices and server respectively; (3) scheduling tasks to mitigate straggler problems and enhance computing utility; (4) distributed client state manager to support various FL algorithms.
Linguistic More: Taking a Further Step toward Efficient and Accurate Scene Text Recognition
Vision model have gained increasing attention due to their simplicity and efficiency in Scene Text Recognition (STR) task.
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
It is a large-scale digital library for head avatars with three key attributes: 1) High Fidelity: all subjects are captured by 60 synchronized, high-resolution 2K cameras in 360 degrees.
From Hypergraph Energy Functions to Hypergraph Neural Networks
Hypergraphs are a powerful abstraction for representing higher-order interactions between entities of interest.
Learning Unified Decompositional and Compositional NeRF for Editable Novel View Synthesis
State-of-the-art methods in this direction typically consider building separate networks for these two tasks (i. e., view synthesis and editing).
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs
The rapid growth of memory and computation requirements of large language models (LLMs) has outpaced the development of hardware, hindering people who lack large-scale high-end GPUs from training or deploying LLMs.
Energy-efficient Integrated Sensing and Communication System and DNLFM Waveform
In this paper, the ISAC system employs dedicated sensing signals, which can be reused as the communication reference signal.
Symmetrical Linguistic Feature Distillation with CLIP for Scene Text Recognition
In this paper, we explore the potential of the Contrastive Language-Image Pretraining (CLIP) model in scene text recognition (STR), and establish a novel Symmetrical Linguistic Feature Distillation framework (named CLIP-OCR) to leverage both visual and linguistic knowledge in CLIP.
Efficient Link Prediction via GNN Layers Induced by Negative Sampling
Graph neural networks (GNNs) for link prediction can loosely be divided into two broad categories.
Joint Detection Algorithm for Multiple Cognitive Users in Spectrum Sensing
This paper first introduces three common logical circuit decision criteria in hard decisions and analyzes their decision rigor.
FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation
Federated learning (FL) is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server.
Optimizing the Passenger Flow for Airport Security Check
Due to the necessary security for the airport and flight, passengers are required to have strict security check before getting aboard.
Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit
Transformer requires a fixed number of layers and heads which makes them inflexible to the complexity of individual samples and expensive in training and inference.
Angle Robustness Unmanned Aerial Vehicle Navigation in GNSS-Denied Scenarios
Due to the inability to receive signals from the Global Navigation Satellite System (GNSS) in extreme conditions, achieving accurate and robust navigation for Unmanned Aerial Vehicles (UAVs) is a challenging task.
Mixer is more than just a model
In the field of computer vision, MLP-Mixer is noted for its ability to extract data information from both channel and token perspectives, effectively acting as a fusion of channel and token information.
Ranked #1 on
Environmental Sound Classification
on UrbanSound8K
Environmental Sound Classification
Speech Emotion Recognition
A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges
The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry.
