Strong convexity-guided hyper-parameter optimization for flatter losses

We propose a novel white-box approach to hyper-parameter optimization. Motivated by recent work establishing a relationship between flat minima and generalization, we first establish a relationship between the strong convexity of the loss and its flatness. Based on this, we seek to find hyper-parameter configurations that improve flatness by minimizing the strong convexity of the loss. By using the structure of the underlying neural network, we derive closed-form equations to approximate the strong convexity parameter, and attempt to find hyper-parameters that minimize it in a randomized fashion. Through experiments on 14 classification datasets, we show that our method achieves strong performance at a fraction of the runtime.Comment: v

An analytical model of prominence dynamics

Solar prominences are magnetic structures incarcerating cool and dense gas in an otherwise hot solar corona. Prominences can be categorized as quiescent and active. Their origin and the presence of cool gas (~$10^4$K) within the hot (~$10^6$K) solar corona remains poorly understood. The structure and dynamics of solar prominences was investigated in a large number of observational and theoretical (both analytical and numerical) studies. In this paper, an analytic model of quiescent solar prominence is developed and used to demonstrate that the prominence velocity increases exponentially, which means that some gas falls downward towards the solar surface, and that Alfven waves are naturally present in the solar prominences. These theoretical predictions are consistent with the current observational data of solar quiescent prominences.Comment: Update Final Journal Print Version along with other Metadat

An Efficient Interference Aware Partially Overlapping Channel Assignment and Routing in Wireless Mesh Networks

In recent years, multi-channel multi-radio wireless mesh networks are considered a reliable and cost effective way for internet access in wide area. A major research challenge in this network is, selecting a least interference channel from the available channels, efficiently assigning a radio to the selected channel, and routing packets through the least interference path. Many algorithms and methods have been developed for channel assignment to maximize the network throughput using orthogonal channels. Recent research and test-bed experiments have proved that POC (Partially Overlapped Channels) based channel assignment allows significantly more flexibility in wireless spectrum sharing. In this paper, first we represent the channel assignment as a graph edge coloring problem using POC. The signal-to-noise plus interference ratio is measured to avoid interference from neighbouring transmissions, when a channel is assigned to the link. Second we propose a new routing metric called signal-to-noise plus interference ratio (SINR) value which measures interference in each link and routing algorithm works based on the interference information. The simulation results show that the channel assignment and interference aware routing algorithm, proposed in this paper, improves the network throughput and performance