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Resilient Level Ancestor, Bottleneck, and Lowest Common Ancestor Queries in Dynamic Trees
We study the problem of designing a resilient data structure maintaining a tree under the Faulty-RAM model [Finocchi and Italiano, STOC’04] in which...
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SUBTLE: An Unsupervised Platform with Temporal Link Embedding that Maps Animal Behavior
While huge strides have recently been made in language-based machine learning, the ability of artificial systems to comprehend the sequences that...
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Breaking the von Neumann bottleneck: architecture-level processing-in-memory technology
The “memory wall” problem or so-called von Neumann bottleneck limits the efficiency of conventional computer architectures, which move data from...
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Link prediction in directed complex networks: combining similarity-popularity and path patterns mining
Discovering new relationships between entities in networked data is essential in various applications such as sociology, security, physics, and...
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A novel cross-network node pair embedding methodology for anchor link prediction
Anchor link prediction across social networks is highly important for multiple social network analysis. Traditional methods rely heavily on...
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Link prediction in food heterogeneous graphs for personalised recipe recommendation based on user interactions and dietary restrictions
Recipe data and user interactions and preferences have been widely studied in food computing, especially for the recipe recommendation task. One part...
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Information Bottleneck Theory on Convolutional Neural Networks
Recent years, many researches attempt to open the black box of deep neural networks and propose a various of theories to understand it. Among them,...
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Link Traversal Query Processing Over Decentralized Environments with Structural Assumptions
To counter societal and economic problems caused by data silos on the Web, efforts such as Solid strive to reclaim private data by storing it in...
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\(M^3\) -IB: A Memory-Augment Multi-modal Information Bottleneck Model for Next-Item Recommendation
Modeling of users and items is essential for accurate recommendations. Traditional methods focused only on users’ behavior data for recommendation....
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GC-LSTM: graph convolution embedded LSTM for dynamic network link prediction
Dynamic network link prediction is becoming a hot topic in network science, due to its wide applications in biology, sociology, economy and industry....
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HOPLoP: multi-hop link prediction over knowledge graph embeddings
Large-scale Knowledge Graphs (KGs) support applications such as Web search and personal assistants and provide training data for numerous Natural...
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A Custom Hardware Architecture for the Link Assessment Problem
Heterogeneous accelerator enhanced computing architectures are a common solution in embedded computing, mainly due to the constraints in energy and...
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Overcoming the Knowledge Bottleneck Using Lifelong Learning by Social Agents
In this position paper we argue that the best way to overcome the notorious knowledge bottleneck in AI is using lifelong learning by social...
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Incremental learning paradigm with privileged information for random vector functional-link networks: IRVFL+
Learning using privileged information (LUPI) paradigm, which pioneered teacher–student interaction mechanism, makes the learning models use...
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Tuning Functional Link Artificial Neural Network for Software Development Effort Estimation
Software development effort estimation (SDEE) is a critical task in project management for accurate planning, staffing, resource allocation,...
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Design of Multi-utility Bottleneck Horn Antenna for Ku-, K-, and Ka-Band Applications
In this paper, we propose the design to accommodate for the Ku-band (12–18 GHz), K-band (18–27 GHz), and Ka-band (26.5–40 GHz) frequency used cases...
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Expected linear round synchronization: the missing link for linear Byzantine SMR
State Machine Replication (SMR) solutions often divide time into rounds, with a designated leader driving decisions in each round. Progress is...
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Link-Efficiency Multi-channel Transmission Protocol for Data Collection in UASNs
With the burgeoning of underwater Internet of things, the amount of data generated by sensor nodes increases dramatically in UASNs, requiring...
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Increasing the Sampling Efficiency for the Link Assessment Problem
Complex graphs are at the heart of today’s big data challenges like recommendation systems, customer behavior modeling, or incident detection...