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06/01/2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
We derive an (almost) guaranteed upper bound on the error of deep neural...
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05/31/2023
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
This paper focuses on supervised and unsupervised online label shift, wh...
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03/01/2023
Fog Device-as-a-Service (FDaaS): A Framework for Service Deployment in Public Fog Environments
Meeting the requirements of future services with time sensitivity and ha...
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02/06/2023
RLSbench: Domain Adaptation Under Relaxed Label Shift
Despite the emergence of principled methods for domain adaptation under ...
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02/06/2023
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets
Open vocabulary models (e.g. CLIP) have shown strong performance on zero...
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11/29/2022
Disentangling the Mechanisms Behind Implicit Regularization in SGD
A number of competing hypotheses have been proposed to explain why small...
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10/26/2022
Characterizing Datapoints via Second-Split Forgetting
Researchers investigating example hardness have increasingly focused on ...
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09/28/2022
Downstream Datasets Make Surprisingly Good Pretraining Corpora
For most natural language processing tasks, the dominant practice is to ...
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07/26/2022
Unsupervised Learning under Latent Label Shift
What sorts of structure might enable a learner to discover classes from ...
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07/26/2022
Domain Adaptation under Open Set Label Shift
We introduce the problem of domain adaptation under Open Set Label Shift...
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07/06/2022
A Comprehensive Review on Deep Supervision: Theories and Applications
Deep supervision, or known as 'intermediate supervision' or 'auxiliary s...
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02/20/2022
Deconstructing Distributions: A Pointwise Framework of Learning
In machine learning, we traditionally evaluate the performance of a sing...
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01/11/2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
Real-world machine learning deployments are characterized by mismatches ...
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12/19/2021
Parallel Multi-Scale Networks with Deep Supervision for Hand Keypoint Detection
Keypoint detection plays an important role in a wide range of applicatio...
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11/01/2021
Mixture Proportion Estimation and PU Learning: A Modern Approach
Given only positive examples and unlabeled examples (from both positive ...
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10/29/2021
SDP: Scalable Real-time Dynamic Graph Partitioner
Time-evolving large graph has received attention due to their participat...
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08/23/2021
Towards a Formal Modelling, Analysis, and Verification of a Clone Node Attack Detection Scheme in the Internet of Things
In a clone node attack, an attacker attempted to physically capture the ...
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06/30/2021
A Context-Aware Information-Based Clone Node Attack Detection Scheme in Internet of Things
The rapidly expanding nature of the Internet of Things (IoT) networks is...
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05/25/2021
A Taxonomy Study on Securing Blockchain-based Industrial Applications: An Overview, Application Perspectives, Requirements, Attacks, Countermeasures, and Open Issues
Blockchain technology has taken on a leading role in today's industrial ...
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05/01/2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization
To assess generalization, machine learning scientists typically either (...
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04/29/2021
Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directions
With populations ageing, the number of people with dementia worldwide is...
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03/10/2021
Multiple Linear Regression-Based Energy-Aware Resource Allocation in the Fog Computing Environment
Fog computing is a promising computing paradigm for time-sensitive Inter...
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03/10/2021
Fuzzy Logic-based Robust Failure Handling Mechanism for Fog Computing
Fog computing is an emerging computing paradigm which is mainly suitable...
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02/20/2021
On Proximal Policy Optimization's Heavy-tailed Gradients
Modern policy gradient algorithms, notably Proximal Policy Optimization ...
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03/17/2020
A Unified View of Label Shift Estimation
Label shift describes the setting where although the label distribution ...
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03/01/2020
Authentication, Access Control, Privacy, Threats and Trust Management Towards Securing Fog Computing Environments: A Review
Fog computing is an emerging computing paradigm that has come into consi...
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12/18/2019
Adaptive Scheduling for Efficient Execution of Dynamic Stream Workflows
Stream workflow application such as online anomaly detection or online t...
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12/18/2019
Scheduling Algorithms for Efficient Execution of Stream Workflow Applications in Multicloud Environments
Big data processing applications are becoming more and more complex. The...
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12/17/2019
Multi-Criteria-based Dynamic User Behaviour Aware Resource Allocation in Fog Computing
Fog computing is a promising computing paradigm in which IoT data can be...
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10/10/2019
BigDataSDNSim: A Simulator for Analyzing Big Data Applications in Software-Defined Cloud Data Centers
Emerging paradigms of big data and Software-Defined Networking (SDN) in ...
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10/07/2019
IoTSim-Edge: A Simulation Framework for Modeling the Behaviour of IoT and Edge Computing Environments
This paper proposes a novel simulator IoTSim-Edge, which captures the be...
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02/05/2019
Window-based Streaming Graph Partitioning Algorithm
In the recent years, the scale of graph datasets has increased to such a...
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11/22/2018
Fog Computing Architecture: Survey and Challenges
Emerging technologies that generate a huge amount of data such as the In...
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09/06/2018
Code-switched Language Models Using Dual RNNs and Same-Source Pretraining
This work focuses on building language models (LMs) for code-switched te...
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07/03/2018
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions
Emerging technologies like the Internet of Things (IoT) require latency-...
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06/20/2018
User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy
Recommender systems have become an integral part of many social networks...
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04/16/2018
Automatic Rain and Cicada Chorus Filtering of Bird Acoustic Data
Recording and analysing environmental audio recordings has become a comm...
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02/02/2018
Scalable Preprocessing of High Volume Bird Acoustic Data
In this work, we examine the problem of efficiently preprocessing high v...
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11/03/2017
