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12th International Conference on Learning Representations, ICLR 2024

作者： Ye, Linfeng Hamidi, Shayan Mohajer Tan, Renhao Yang, En-Hui Department of Electrical and Computer Engineering University of Waterloo Canada

It is believed that in knowledge distillation (KD), the role of the teacher is to provide an estimate for the unknown Bayes conditional probability distribution (BCPD) to be used in the student training process. Conventionally, this estimate is obtained by training the teacher using maximum log-likelihood (MLL) method. To improve this estimate for KD, in this paper we introduce the concept of conditional mutual information (CMI) into the estimation of BCPD and propose a novel estimator called the maximum CMI (MCMI) method. Specifically, in MCMI estimation, both the log-likelihood and CMI of the teacher are simultaneously maximized when the teacher is trained. Through Eigen-CAM, it is further shown that maximizing the teacher's CMI value allows the teacher to capture more contextual information in an image cluster. Via conducting a thorough set of experiments, we show that by employing a teacher trained via MCMI estimation rather than one trained via MLL estimation in various state-of-the-art KD frameworks, the student's classification accuracy consistently increases, with the gain of up to 3.32%. This suggests that the teacher's BCPD estimate provided by MCMI method is more accurate than that provided by MLL method. In addition, we show that such improvements in the student's accuracy are more drastic in zero-shot and few-shot settings. Notably, the student's accuracy increases with the gain of up to 5.72% when 5% of the training samples are available to the student (few-shot), and increases from 0% to as high as 84% for an omitted class (zero-shot). The code is available at https://***/iclr2024mcmi/ICLRMCMI. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Distillation

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AMVP Candidate List Construction With Zero Motion Vector for Beyond VVC

AMVP Candidate List Construction With Zero Motion Vector for...

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2025 International Workshop on Advanced Imaging Technology, IWAIT 2025

作者： Park, Seori Jeon, Byeungwoo Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

ISBN: (数字)9781510688131

ISBN: (纸本)9781510688124

Completing standardization of the VVC in July 2020, the Joint Video Experts Team of ISO/IEC SC29/WG05 launched the "Beyond VVC" exploration by developing the Enhanced Compression Model (ECM) which keeps integrating newly developed advanced encoding tools *** inter prediction, the Advanced Motion Vector Prediction (AMVP) method encodes motion vectors using Motion Vector Predictor (MVP) selected from MVP candidate *** the current ECM of version 11.0, unless zero MV is added at the first place into the candidate list while at least one neighboring block has zero MV, zero MV has very low probability to be selected as MVP, thus potentially resulting in reduced coding *** overcome this limitation, we investigate a method that puts zero MV into the list unless the list is already full so that the zero MV can be subject to MVP refinement and reordering process to improve coding *** results demonstrate BDBR gain of 0.03% in the luma channel. © 2024 SPIE.

关键词： ISO Standards

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The Role of Artificial Intelligence in Idea Management Systems and Innovation Processes: An Integrative Review

The Role of Artificial Intelligence in Idea Management Syste...

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Leka, Serena Department of Electrical and Computer Engineering Aarhus University Denmark

ISBN: (纸本)9798400716928

The role of artificial intelligence (AI) in idea management systems (IMS) and innovation processes has recently been a topic of significant research interest. AI has been acknowledged for its potential to enhance innovation activities by providing support in various aspects. The intersection of these areas offers promising opportunities for improved idea generation, classification, development, and evaluation. However, AI's impact is not equally present for the different stages of an innovation process, showing more prominence in the idea generation stage. Through an integrative review, we can explore how AI has contributed to different steps of innovation processes implemented through IMS. AI-driven approaches, so far, have been opening possibilities to manage creative processes, such as automating specific tasks, analyzing large amounts of data to identify patterns and trends, and providing real-time feedback to enhance ideation and decision-making. Assessing the contribution of AI to innovation and creativity is vital in understanding its potential influence on the future developments of IMS and innovation processes. © 2024 Owner/Author.

关键词： Artificial intelligence

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Robust Regression with Ensembles Communicating over Noisy Channels

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IEEE Journal on Selected Areas in Communications 2025年第7期43卷 2714-2727页

作者： Ben-Hur, Yuval Cassuto, Yuval Technion-Israel Institute of Technology Haifa Israel Viterbi Department of Electrical and Computer Engineering Technion - Israel Institute of Technology

As machine-learning models grow in size, their implementation requirements cannot be met by a single computer system. This observation motivates distributed settings, in which intermediate computations are performed across a network of processing units, while the central node only aggregates their outputs. However, distributing inference tasks across low-precision or faulty edge devices, operating over a network of noisy communication channels, gives rise to serious reliability challenges. We study the problem of an ensemble of devices, implementing regression algorithms, that communicate through additive noisy channels in order to collaboratively perform a joint regression task. We define the problem formally, and develop methods for optimizing the aggregation coefficients for the parameters of the noise in the channels, which can potentially be correlated. Our results apply to the leading state-of-the-art ensemble regression methods: bagging and gradient boosting. We demonstrate the effectiveness of our algorithms on both synthetic and real-world datasets. © 1983-2012 IEEE.

关键词： Contrastive Learning

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Machine Learning-Enhanced Overcoupled Plasmonic Resonators for Biomolecular Detection 38

Machine Learning-Enhanced Overcoupled Plasmonic Resonators f...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Li, Dongxiao Zhou, Hong Ren, Zhihao Xu, Cheng Lee, Chengkuo National University of Singapore Department of Electrical & Computer Engineering Singapore

ISBN: (纸本)9798331508890

Plasmonic biosensors offer a unique opportunity to precisely control light-matter coupling in surface-enhanced infrared absorption (SEIRA) spectroscopy. However, the broadband nature of infrared spectra and the complex molecular information pose challenges in detecting and distinguishing biomolecules. Here, we propose the design of an overcoupled plasmonic resonator with ultrasensitive (7.25%/nm) and ultrabroadband (1000-3333 cm-1) sensing capabilities. These features allow the resonator to enhance multiple molecular fingerprint vibrations with high sensitivity. To further unlock the sensor's potential, machine learning is employed, achieving 100% accuracy in identifying five biomolecules based on rich vibrational data. With outstanding sensing performance and molecular recognition capabilities, the machine-learning-enhanced overcoupled resonator paves the way for broader SEIRA applications. © 2025 IEEE.

关键词： Infrared absorption

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Intermediate Layer Distillation with the Reused Teacher Classifier: A Study on the Importance of the Classifier of Attention-based Models

Intermediate Layer Distillation with the Reused Teacher Clas...

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2024 Findings of the Association for Computational Linguistics, EMNLP 2024

作者： Zhang, Hang Mozafari, Seyyed Hasan Clark, James J. Meyer, Brett H. Gross, Warren J. Department of Electrical and Computer Engineering McGill University Canada

ISBN: (纸本)9798891761681

Intermediate Layer Distillation (ILD) effectively compresses large-scale pre-trained language models (PLMs). Existing ILD methods underestimate the importance of utilizing the teacher's discriminative classifier and face challenges in establishing proper layer mappings. Therefore, we propose ILD-RTC, to show that a straightforward implementation of reusing the pre-trained teacher classifier improves student performance even with simple uniform layer mapping. Through extensive experiments, our method outperforms other ILD techniques, maintaining 97.7% performance of the original teacher BERTbase without additional trainable parameters. Projectors are developed to help the student match the hidden size of the teacher model, making our ILD-RTC applicable to students with different sizes. In addition, our technique achieves the same average GLUE score as students initialized by pre-trained LMs, saving over 80× cost resulting from the pre-training step. Our method emphasizes the reuse of pre-trained teacher classifiers as an alternative to pre-training the student for initialization. © 2024 Association for Computational Linguistics.

关键词： Students

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Delay Towers to Bootstrap Blockchains 6

Delay Towers to Bootstrap Blockchains

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6th IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2024

作者： Motepalli, Shashank Jacobsen, Hans-Arno University of Toronto Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350316742

To bolster Sybil resistance and establish persistent identities in new permissionless blockchain networks, we introduce delay towers, leveraging Verifiable Delay Functions (VDFs) to implement a proof of elapsed time (PoET). By utilizing inherently sequential cryptographic primitives, delay towers present an eco-friendly alternative to traditional PoW and PoS mechanisms, enabling sustainable network growth without reliance on token sales or airdrops. This work not only considers the blockchain's ecological footprint but also upholds the principles of a fair launch to enable a decentralized blockchain ecosystem. © 2024 IEEE.

关键词： Blockchain

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A Novel Circularly-Polarized Microstrip Antenna by Coupled Resonators

A Novel Circularly-Polarized Microstrip Antenna by Coupled R...

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2024 IEEE International Workshop on Wireless Sensing Technologies and Applications, IWSA 2024

作者： Hao, Jia-Xiang Zhu, Lei University of Macau Department of Electrical and Computer Engineering China

ISBN: (纸本)9798331505837

This paper proposes a circularly-polarized (CP) antenna through coupling effects. By orthogonally arranging the short-circuited (open-circuited) ends of two identical λ/4 short-circuited microstrip line (MS-L) resonators to each other, the CP radiation by magnetic(electric) coupling can be produced. Then, for improving the peak gain and the axial ratio bandwidth (ARBW), a binary array comprising of an electrically coupled (EC) pair and a magnetically coupled (MC) pair of resonators is presented. Then the array is fabricated, and an excellent agreement between the experiment and simulation results is validated. © 2024 IEEE.

关键词： Circular polarization

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SNR Enhancement using Sub-Array-Based Processing with Application to Millimeter Wave Imaging at W-Band

SNR Enhancement using Sub-Array-Based Processing with Applic...

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2025 IEEE Radio and Wireless Symposium, RWS 2025

作者： Hamidi, Shahrokh Nezhad-Ahmadi, M.R. University of Waterloo Department of Electrical and Computer Engineering WaterlooON Canada

ISBN: (纸本)9798350377743

High resolution radar imaging at millimeter wave frequencies is of high importance. To achieve high resolution in range direction, large bandwidth is utilized. However, generating high output power at millimeter wave frequencies over large bandwidth is challenging. In this paper, we present a novel technique at the signal processing level to increase the Signal to Noise Ratio (SNR). This is considered a significant achievement since path loss attenuation at millimeter wave frequencies reduces the SNR considerably. The proposed method is based on sub-array signal processing. Finally, we collect data from our wide-band custom-made Frequency Modulated Continuous Wave (FMCW) radar, operating at W-band with 33 GHz bandwidth, to demonstrate the overall effectiveness of the proposed approach in SNR enhancement. © 2025 IEEE.

关键词： Image enhancement

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SUMIT: Secure Unicast and Multicast Communication in Internet of Mobile Things

SUMIT: Secure Unicast and Multicast Communication in Interne...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Reefat, Hasin Ishraq Ebrahimabadi, Mohammad Younis, Mohamed Alkanhal, Mona Karimi, Naghmeh Department of Computer Science and Electrical Engineering United States

ISBN: (纸本)9798350351255

An Internet of Mobile Things (IoMT) refers to an internetworked group of pervasive devices that coordinate their motion and task execution through frequent status and data exchange. An IoMT could be serving critical applications such as military reconnaissance, security surveillance, etc., and hence the authenticity, integrity and confidentiality of the transmitted data must be ensured. Yet, achieving the security goals is challenging due to the dynamic nature of the network topology, the constrained computational and communication resources, and the variety of packet traffic patterns among the nodes. This paper proposes an effective solution that leverages lightweight hardware primitives, specifically, Physical Unclonable Functions (PUFs), to support secure communication in the network. The employed PUFs are used to generate peer-to-peer encryption keys to protect the data traffic among nodes and to the command center, while coping with the dynamic change of the network topology. Our solution efficiently supports both unicast and multicast communications. The proposed solution is validated through analysis and prototype implementation on an FPGA. © 2024 IEEE.

关键词： Secure communication

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