Communication-Oriented Model Fine-Tuning for Packet-Loss Resilient Distributed Inference Under Highly Lossy IoT Networks

The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained Internet of things (IoT) devices. In DI, computational tasks are offloaded from the IoT device to the edge server via lossy IoT networks. However, generally, there is a communication system-level trade-off between communication latency and reliability; thus, to provide accurate DI results, a reliable and high-latency communication system is required to be adapted, which results in non-negligible end-to-end latency of the DI. This motivated us to improve the trade-off between the communication latency and accuracy by efforts on ML techniques. Specifically, we have proposed a communication-oriented model tuning (COMtune), which aims to achieve highly accurate DI with low-latency but unreliable communication links. In COMtune, the key idea is to fine-tune the ML model by emulating the effect of unreliable communication links through the application of the dropout technique. This enables the DI system to obtain robustness against unreliable communication links. Our ML experiments revealed that COMtune enables accurate predictions with low latency and under lossy networks

Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data

This study develops a federated learning (FL) framework overcoming largely incremental communication costs due to model sizes in typical frameworks without compromising model performance. To this end, based on the idea of leveraging an unlabeled open dataset, we propose a distillation-based semi-supervised FL (DS-FL) algorithm that exchanges the outputs of local models among mobile devices, instead of model parameter exchange employed by the typical frameworks. In DS-FL, the communication cost depends only on the output dimensions of the models and does not scale up according to the model size. The exchanged model outputs are used to label each sample of the open dataset, which creates an additionally labeled dataset. Based on the new dataset, local models are further trained, and model performance is enhanced owing to the data augmentation effect. We further highlight that in DS-FL, the heterogeneity of the devices’ dataset leads to ambiguous of each data sample and lowing of the training convergence. To prevent this, we propose entropy reduction averaging, where the aggregated model outputs are intentionally sharpened. Moreover, extensive experiments show that DS-FL reduces communication costs up to 99 percent relative to those of the FL benchmark while achieving similar or higher classification accuracy

A common behavior of thermoelectric layered cobaltites: incommensurate spin density wave states in [Ca2_2Co4/3_{4/3}Cu2/3_{2/3}O4_4]0.62_{0.62}[CoO2_2] and [Ca2_2CoO3_3]0.62_{0.62}[CoO2_2]

Magnetism of a misfit layered cobaltite [Ca$_2$Co$_{4/3}$Cu$_{2/3}$O$_4$]$_x^{\rm RS}$[CoO$_2$] ($x \sim$ 0.62, RS denotes a rocksalt-type block) was investigated by a positive muon spin rotation and relaxation ($\mu^+$SR) experiment. A transition to an incommensurate ({\sf IC}) spin density wave ({\sf SDW}) state was found below 180 K (= $T_{\rm C}^{\rm on}$); and a clear oscillation due to a static internal magnetic field was observed below 140 K (= $T_{\rm C}$). Furthermore, an anisotropic behavior of the zero-field $\mu^+$SR experiment indicated that the {\sf IC-SDW} propagates in the $a$-$b$ plane, with oscillating moments directed along the c axis. These results were quite similar to those for the related compound [Ca$_2$CoO$_3$]$_{0.62}^{\rm RS}$[CoO$_2$], {\sl i.e.}, Ca$_3$Co$_4$O$_9$. Since the {\sf IC-SDW} field in [Ca$_2$Co$_{4/3}$Cu$_{2/3}$O$_4$]$_{0.62}^{\rm RS}$[CoO$_2$] was approximately same to those in pure and doped [Ca$_2$CoO$_3$]$_{0.62}^{\rm RS}$[CoO$_2$], it was concluded that the {\sf IC-SDW} exist in the [CoO$_2$] planes.Comment: 15 pages, 6 figures. accepted for publication in J. Phys.: Condens. Matte

Hidden magnetic transitions in thermoelectric layered cobaltite, [Ca2_2CoO3_3]0.62_{0.62}[CoO2_2]

A positive muon spin rotation and relaxation ($\mu^+$SR) experiment on [Ca$_2$CoO$_3$]$_{0.62}$[CoO$_2$], ({\sl i.e.}, Ca$_3$Co$_4$O$_9$, a layered thermoelectric cobaltite) indicates the existence of two magnetic transitions at $\sim$ 100 K and 400 - 600 K; the former is a transition from a paramagnetic state to an incommensurate ({\sf IC}) spin density wave ({\sf SDW}) state. The anisotropic behavior of zero-field $\mu^+$SR spectra at 5 K suggests that the {\sf IC-SDW} propagates in the $a$-$b$ plane, with oscillating moments directed along the c-axis; also the {\sf IC-SDW} is found to exist not in the [Ca$_2$CoO$_3$] subsystem but in the [CoO$_2$] subsystem. In addition, it is found that the long-range {\sf IC-SDW} order completes below $\sim$ 30 K, whereas the short-range order appears below 100 K. The latter transition is interpreted as a gradual change in the spin state of Co ions %% at temperatures above 400 K. These two magnetic transitions detected by $\mu^+$SR are found to correlate closely with the transport properties of [Ca$_2$CoO$_3$]$_{0.62}$[CoO$_2$].Comment: 7 pages, 8 figures. to be appeared in Phys. Rev.

Palladium-catalyzed direct C-H functionalization of benzoquinone

A direct Pd-catalyzed C=H functionalization of benzoquinone (BQ) can be controlled to give either mono- or disubstituted BQ, including the installation of two different groups in a one-pot procedure. BQ can now be directly functionalized with aryl, heteroaryl, cycloalkyl, and cycloalkene groups and, moreover, the reaction is conducted in environmentally benign water or acetone as solvents