Context-aware intelligence in resource-constrained IoT nodes: Opportunities and challenges
Editor's note: This article provides an academic perspective of the problem, starting with a
survey of recent advances in intelligent sensing, computation, communication, and energy …
survey of recent advances in intelligent sensing, computation, communication, and energy …
A survey of on-device machine learning: An algorithms and learning theory perspective
The predominant paradigm for using machine learning models on a device is to train a
model in the cloud and perform inference using the trained model on the device. However …
model in the cloud and perform inference using the trained model on the device. However …
Learning from reviews: The selection effect and the speed of learning
This paper develops a model of Bayesian learning from online reviews and investigates the
conditions for learning the quality of a product and the speed of learning under different …
conditions for learning the quality of a product and the speed of learning under different …
Fake news propagation and detection: A sequential model
Y Papanastasiou - Management Science, 2020 - pubsonline.informs.org
In the wake of the 2016 US presidential election, social-media platforms are facing
increasing pressure to combat the propagation of “fake news”(ie, articles whose content is …
increasing pressure to combat the propagation of “fake news”(ie, articles whose content is …
Learning how to communicate in the Internet of Things: Finite resources and heterogeneity
For a seamless deployment of the Internet of Things (IoT), there is a need for self-organizing
solutions to overcome key IoT challenges that include data processing, resource …
solutions to overcome key IoT challenges that include data processing, resource …
Distributed detection: Finite-time analysis and impact of network topology
S Shahrampour, A Rakhlin… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
This paper addresses the problem of distributed detection in multi-agent networks. Agents
receive private signals about an unknown state of the world. The underlying state is globally …
receive private signals about an unknown state of the world. The underlying state is globally …
Fast and slow learning from reviews
This paper develops a model of Bayesian learning from online reviews, and investigates the
conditions for asymptotic learning of the quality of a product and the speed of learning under …
conditions for asymptotic learning of the quality of a product and the speed of learning under …
Distributed learning for low latency machine type communication in a massive Internet of Things
The Internet of Things (IoT) will encompass a massive number of machine type devices that
must wirelessly transmit, in near real-time, a diverse set of messages sensed from their …
must wirelessly transmit, in near real-time, a diverse set of messages sensed from their …
Seeding the herd: Pricing and welfare effects of social learning manipulation
L Chen, Y Papanastasiou - Management Science, 2021 - pubsonline.informs.org
This paper is motivated by the recent emergence of various interference tactics employed by
sellers attempting to manipulate social learning. We revisit the classic model of …
sellers attempting to manipulate social learning. We revisit the classic model of …
Social learning with Bayesian agents and random decision making
Y Wang, PM Djurić - IEEE Transactions on Signal Processing, 2015 - ieeexplore.ieee.org
In this paper, we study the effect of randomness in the decision making of agents on social
learning. In the addressed system, the agents make decisions sequentially about the true …
learning. In the addressed system, the agents make decisions sequentially about the true …