3.6k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Inception Institute of Artificial IntelligenceAE16 papers
- Carnegie Mellon UniversityUS15 papers
- École PolytechniqueFR11 papers
- Australian National UniversityAU10 papers
- Nankai UniversityCN8 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR7 papers
- Nanyang Technological UniversitySG7 papers
- National Research University Higher School of EconomicsRU7 papers
- The University of SydneyAU7 papers
- University of WaterlooCA7 papers
- Hamad bin Khalifa UniversityQA6 papers
- Moscow Institute of Physics and TechnologyRU6 papers
19 papers · 1 filter
Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection
Yu Hong, Hang Dai, Yong Ding
Leveraging LiDAR-based detectors or real LiDAR point data to guide monocular 3D detection has brought significant improvement, e.g., Pseudo-LiDAR methods. However, the existing met…
Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation
Florinel-Alin Croitoru, Nicolae-Catalin Ristea, Dana Dascalescu +3
We propose a very fast frame-level model for anomaly detection in video, which learns to detect anomalies by distilling knowledge from multiple highly accurate object-level teacher…
Randomized gradient-free methods in convex optimization
Alexander Gasnikov, Darina Dvinskikh, Pavel Dvurechensky +3
This review presents modern gradient-free methods to solve convex optimization problems. By gradient-free methods, we mean those that use only (noisy) realizations of the objective…
Grammatical Error Correction: A Survey of the State of the Art
Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib +3
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as mi…
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity
Eduard Gorbunov, Adrien Taylor, Samuel Horváth +1
Algorithms for min-max optimization and variational inequalities are often studied under monotonicity assumptions. Motivated by non-monotone machine learning applications, we follo…
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection
Neelu Madan, Nicolae-Catalin Ristea, Radu Tudor Ionescu +4
Anomaly detection has recently gained increasing attention in the field of computer vision, likely due to its broad set of applications ranging from product fault detection on indu…
RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systems
Emna Baccour, Aiman Erbad, Amr Mohamed +2
Although Deep Neural Networks (DNN) have become the backbone technology of several ubiquitous applications, their deployment in resource-constrained machines, e.g., Internet of Thi…
Asymmetric Dual-Mode Constellation and Protograph LDPC Code Design for Generalized Spatial MPPM Systems
Liang Lv, Yi Fang, Lin Dai +2
To achieve reliable and efficient transmissions in free-space optical (FSO) communication, this paper designs a new protograph low-density parity-check (PLDPC) coded generalized sp…
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation
Gongjie Zhang, Zhipeng Luo, Kaiwen Cui +2
Few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is still c…
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing
Wei Xu, Zhaohui Yang, Derrick Wing Kwan Ng +3
To process and transfer large amounts of data in emerging wireless services, it has become increasingly appealing to exploit distributed data communication and learning. Specifical…
Stochastic Gradient Methods with Preconditioned Updates
Abdurakhmon Sadiev, Aleksandr Beznosikov, Abdulla Jasem Almansoori +3
This work considers the non-convex finite sum minimization problem. There are several algorithms for such problems, but existing methods often work poorly when the problem is badly…
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
Peng Zheng, Huazhu Fu, Deng-Ping Fan +5
In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in na…
Design of a Reconfigurable Intelligent Surface-Assisted FM-DCSK-SWIPT Scheme with Non-linear Energy Harvesting Model
Yi Fang, Yiwei Tao, Huan Ma +2
In this paper, we propose a reconfigurable intelligent surface (RIS)-assisted frequency-modulated (FM) differential chaos shift keying (DCSK) scheme with simultaneous wireless info…
A Survey on Applications of Cache-Aided NOMA
Dipen Bepari, Soumen Mondal, Aniruddha Chandra +4
Contrary to orthogonal multiple-access (OMA), non-orthogonal multiple-access (NOMA) schemes can serve a pool of users without exploiting the scarce frequency or time domain resourc…
Artificial Intelligence for 6G Networks: Technology Advancement and Standardization
Muhammad K. Shehzad, Luca Rose, M. Majid Butt +3
With the deployment of 5G networks, standards organizations have started working on the design phase for sixth-generation (6G) networks. 6G networks will be immensely complex, requ…
Internet of Things Device Capabilities, Architectures, Protocols, and Smart Applications in Healthcare Domain: A Review
Md. Milon Islam, Sheikh Nooruddin, Fakhri Karray +1
Nowadays, the Internet has spread to practically every country around the world and is having unprecedented effects on people's lives. The Internet of Things (IoT) is getting more…
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm
Qingsong Zhang, Bin Gu, Zhiyuan Dang +2
Vertical federated learning (VFL) attracts increasing attention due to the emerging demands of multi-party collaborative modeling and concerns of privacy leakage. A complete list o…
Human Activity Recognition Using Tools of Convolutional Neural Networks: A State of the Art Review, Data Sets, Challenges and Future Prospects
Md. Milon Islam, Sheikh Nooruddin, Fakhri Karray +1
Human Activity Recognition (HAR) plays a significant role in the everyday life of people because of its ability to learn extensive high-level information about human activity from…
Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey
Aoran Xiao, Jiaxing Huang, Dayan Guan +3
Point cloud data have been widely explored due to its superior accuracy and robustness under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved very i…