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๐Ÿ” avoidance learning ๐Ÿ“‚ Computer Science
Showing 46580 results for "avoidance learning" in Computer Science
Computer Science Preprint PDF DOI

PulmoVec: A Two-Stage Stacking Meta-Learning Architecture Built on the HeAR Foundation Model for Multi-Task Classification of Pediatric Respiratory Sounds

Izzet Turkalp Akbasli, Oguzhan Serin ยท 2026

Background: Respiratory diseases are a leading cause of childhood morbidity and mortality, yet lung auscultation remains subjective and limited by inter-listener variability, particularly in pediatricโ€ฆ

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Computer Science Preprint PDF DOI

Machine Learning-Driven Intelligent Memory System Design: From On-Chip Caches to Storage

Rahul Bera, Rakesh Nadig, Onur Mutlu ยท 2026

Despite the data-rich environment in which memory systems of modern computing platforms operate, many state-of-the-art architectural policies employed in the memory system rely on static, human-designโ€ฆ

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Computer Science Preprint PDF DOI

Covariance-Guided Resource Adaptive Learning for Efficient Edge Inference

Ahmad N. L. Nabhaan, Zaki Sukma, Rakandhiya D. Rachmanto, Muhammad Husni Santriaji, Byungjin Cho, Arief Setyanto, In Kee Kim ยท 2026

For deep learning inference on edge devices, hardware configurations achieving the same throughput can differ by 2$\times$ in power consumption, yet operators often struggle to find the efficient onesโ€ฆ

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Computer Science Preprint PDF DOI

Tap-to-Adapt: Learning User-Aligned Response Timing for Speech Agents

Zihong He, Hai-Ning Liang, Chen Liang ยท 2026

Response timing judgment is a critical component of interactive speech agents. Although there exists substantial prior work on turn modeling and voice wake-up, there is a lack of research on response โ€ฆ

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Computer Science Preprint PDF DOI

Affectron: Emotional Speech Synthesis with Affective and Contextually Aligned Nonverbal Vocalizations

Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim, Seong-Whan Lee ยท 2026

Nonverbal vocalizations (NVs), such as laughter and sighs, are central to the expression of affective cues in emotional speech synthesis. However, learning diverse and contextually aligned NVs remainsโ€ฆ

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Computer Science Preprint PDF DOI

Learning Image-Text Matching with Optimal Partial Transport

Zhengxin Pan, Haishuai Wang, Fangyu Wu, Bailing Zhang, Jiajun Bu, Hongyang Chen ยท 2026

Cross-modal matching, a fundamental task in bridging vision and language, has recently garnered substantial research interest. Despite the development of numerous methods aimed at quantifying the semaโ€ฆ

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DeepOFW: Deep Learning-Driven OFDM-Flexible Waveform Modulation for Peak-to-Average Power Ratio Reduction

Ran Greidi, Kobi Cohen ยท 2026

Peak-to-average power ratio (PAPR) remains a major limitation of multicarrier modulation schemes such as orthogonal frequency-division multiplexing (OFDM), reducing power amplifier efficiency and limiโ€ฆ

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What Are You Really Asking For? A Comparative 5W1H Analysis of Learner Questioning in CPR Training with IVAs in Screen-based and Augmented Reality Environments

Hyerim Park, Jinseok Hong, Heejeong Ko, Woontack Woo ยท 2026

Question-asking is one of the key indicators of cognitive engagement. However, understanding how the distinct psychological affordances of presentation media shape learners' spoken inquiries with emboโ€ฆ

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ITKIT: Feasible CT Image Analysis based on SimpleITK and MMEngine

Yiqin Zhang, Meiling Chen ยท 2026

CT images are widely used in clinical diagnosis and treatment, and their data have formed a de facto standard - DICOM. It is clear and easy to use, and can be efficiently utilized by data-driven analyโ€ฆ

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Experimental Evaluation of Security Attacks on Self-Driving Car Platforms

Viet K. Nguyen, Nathan Lee, Mohammad Husain ยท 2026

Deep learning-based perception pipelines in autonomous ground vehicles are vulnerable to both adversarial manipulation and network-layer disruption. We present a systematic, on-hardware experimental eโ€ฆ

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DeepFix: Debugging and Fixing Machine Learning Workflow using Agentic AI

Fadel Mamar Seydou, Arnab Sharma ยท 2026

In recent years, machine learning (ML) based software systems are increasingly deployed in several critical applications, yet systematic testing of their behavior remains challenging due to complex moโ€ฆ

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A Machine Learning Framework for Constructing Heterogeneous Contact Networks: Implications for Epidemic Modelling

Luke Murray Kearney, Emma L Davis, Matt J Keeling ยท 2026

Capturing the structured mixing within a population is key to the reliable projection of infectious disease dynamics and hence informed control. Both heterogeneity in the number of contacts and age-stโ€ฆ

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What Counts as Real? Speech Restoration and Voice Quality Conversion Pose New Challenges to Deepfake Detection

Shree Harsha Bokkahalli Satish, Harm Lameris, Joakim Gustafson, Eva Szekely ยท 2026

Audio anti-spoofing systems are typically formulated as binary classifiers distinguishing bona fide from spoofed speech. This assumption fails under layered generative processing, where benign transfoโ€ฆ

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Deep Learning for Virtual Reality User Identification: A Benchmark

Davide Frizzo, Fabrizio Genilotti, David Petrovic, Arianna Stropeni, Francesco Borsatti, Davide Dalle Pezze, Riccardo De Monte, Manuel Barusco, Gian Antonio Susto ยท 2026

Virtual Reality (VR) applications require robust user identification systems to ensure secure access to equipment and protect worker identities. Motion tracking data from VR headsets and controllers hโ€ฆ

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LLM-Guided Reinforcement Learning for Audio-Visual Speech Enhancement

Chih-Ning Chen, Jen-Cheng Hou, Hsin-Min Wang, Shao-Yi Chien, Yu Tsao, Fan-Gang Zeng ยท 2026

In existing Audio-Visual Speech Enhancement (AVSE) methods, objectives such as Scale-Invariant Signal-to-Noise Ratio (SI-SNR) and Mean Squared Error (MSE) are widely used; however, they often correlatโ€ฆ

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Iterative Semantic Reasoning from Individual to Group Interests for Generative Recommendation with LLMs

Xiaofei Zhu, Jinfei Chen, Feiyang Yuan, Zhou Yang ยท 2026

Recommendation systems aim to learn user interests from historical behaviors and deliver relevant items. Recent methods leverage large language models (LLMs) to construct and integrate semantic represโ€ฆ

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MLFCIL: A Multi-Level Forgetting Mitigation Framework for Federated Class-Incremental Learning in LEO Satellites

Heng Zhang, Xiaohong Deng, Sijing Duan, Wu Ouyang, KM Mahfujul, Yiqin Deng, Zhigang Chen ยท 2026

Low-Earth-orbit (LEO) satellite constellations are increasingly performing on-board computing. However, the continuous emergence of new classes under strict memory and communication constraints poses โ€ฆ

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Calibrating Microgrid Simulations for Energy-Aware Computing Systems

Marvin Steinke ยท 2026

The surge for computing resource demand is increasing global electricity consumption in data centers which is expected to exceed 1000 TWh by 2026, mainly attributable to adoption of new AI technologieโ€ฆ

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EVNextTrade: Learning-to-Rank-Based Recommendation of Next Charging Nodes for EV-EV Energy Trading

Md Mahfujur Rahmana, Alistair Barros, Raja Jurdak, Darshika Koggalahewa ยท 2026

Peer-to-peer energy trading among electric vehicles (EVs) has been increasingly studied as a promising solution for improving supply-side resilience under growing charging demand and constrained chargโ€ฆ

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ATCC: Adaptive Concurrency Control for Unforeseen Agentic Transactions

Weixing Zhou, Zhiyou Wang, Zeshun Peng, Hetian Chen, Yanfeng Zhang, Ge Yu ยท 2026

Data agents, empowered by Large Language Models (LLMs), introduce a new paradigm in transaction processing. Unlike traditional applications with fixed patterns, data agents run online-generated workflโ€ฆ

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