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Advances and Open Problems in Federated Learning
TLDR
Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges. Expand
Optimality of Myopic Sensing in Multichannel Opportunistic Access
TLDR
It is shown that a myopic policy that maximizes the immediate one-step reward is optimal when the state transitions are positively correlated over time and when the number of channels is limited to two or three, while presenting a counterexample for the case of four channels. Expand
Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification
TLDR
Evaluation on person attributes classification tasks involving facial and clothing attributes suggests that the models produced by the proposed method are fast, compact and can closely match or exceed the state-of-the-art accuracy from strong baselines by much more expensive models. Expand
A high-throughput scheduling algorithm for a buffered crossbar switch fabric
TLDR
It is shown, through fluid model techniques, that this system achieves 100% throughput for input traffic that satisfies the strong law of large numbers and that produces a load /spl les/1/N for any input/output pair of an N/spl times/N switching fabric. Expand
Social learning and distributed hypothesis testing
TLDR
Under mild assumptions, the belief of any agent in any incorrect parameter converges to zero exponentially fast, and the exponential rate of learning is a characterized by the network structure and the divergences between the observations' distributions. Expand
Active Sequential Hypothesis Testing
TLDR
Lower bounds for the optimal total cost are established using results in dynamic programming and the fundamental limits on the maximum achievable information acquisition rate and the optimal reliability are characterized. Expand
Wiretap Channel With Secure Rate-Limited Feedback
TLDR
It is shown that the secrecy capacity, the maximum data rate of reliable communication while the intended message is not revealed to the eavesdropper, is upper bounded as Cs(Rf) les maxmin/p(x) {I(X;Y), I( X;Y |Z) + Rf}. Expand
Optimal Pricing to Manage Electric Vehicles in Coupled Power and Transportation Networks
TLDR
A scheme in which independent power and transportation system operators can collaborate to manage each network towards a socially optimum operating point while keeping the operational data of each system private is proposed. Expand
Optimality of Myopic Sensing in Multi-Channel Opportunistic Access
TLDR
It is shown in this paper that the myopic policy, with a simple and robust structure, achieves optimality under certain conditions and finds applications in opportunistic communications in fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and anti-jamming. Expand
Active Learning and CSI Acquisition for mmWave Initial Alignment
TLDR
This paper establishes the first practically viable solution for initial access and, hence, the first demonstration of stand-alone mmWave communication in the relevant regime of low (−10 dB to +5 dB) raw SNR. Expand
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