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Found 9 papers, 0 papers with code
A Method For Bounding Tail Probabilities
We provide some examples of good candidates for the function $g_X(x)$.
A New Type Of Upper And Lower Bounds On Right-Tail Probabilities Of Continuous Random Variables
In this paper, I present a completely new type of upper and lower bounds on the right-tail probabilities of continuous random variables with unbounded support and with semi-bounded support from the left.
New Bounds on the Accuracy of Majority Voting for Multi-Class Classification
In this paper, we derive a new upper bound on the accuracy of the MVF for the multi-class classification problem.
UB3: Best Beam Identification in Millimeter Wave Systems via Pure Exploration Unimodal Bandits
In this paper, we develop an algorithm that exploits the unimodal structure of the received signal strengths of the beams to identify the best beam in a finite time using pure exploration strategies.
Learning Optimal Phase-Shifts of Holographic Metasurface Transceivers
Holographic metasurface transceivers (HMT) is an emerging technology for enhancing the coverage and rate of wireless communication systems.
Parametric Channel Model Estimation for Large Intelligent Surface-Based Transceiver-assisted Communication System
A promising approach for enhancing the coverage and rate of wireless communication systems is the large intelligent surface-based transceiver (LISBT), which uses a spatially continuous surface for signal transmission and receiving.
Learning to Optimize Energy Efficiency in Energy Harvesting Wireless Sensor Networks
We study wireless power transmission by an energy source to multiple energy harvesting nodes with the aim to maximize the energy efficiency.
On Supervised Classification of Feature Vectors with Independent and Non-Identically Distributed Elements
In this paper, we investigate the problem of classifying feature vectors with mutually independent but non-identically distributed elements.
Inference over Wireless IoT Links with Importance-Filtered Updates
We propose a data filtering scheme employed by the IoT nodes, which we refer to as distributed importance filtering in order to filter out redundant data samples already at the IoT nodes.
