Dataset Distillation: A Comprehensive Review

Recent success of deep learning is largely attributed to the sheer amount of data used for training deep neural networks.Despite the unprecedented success, the massive data, unfortunately, significantly increases the burden on storage and transmission and further gives rise to a cumbersome model training process. Besides, relying on the raw data for training \emph{per se} yields concerns about privacy and copyright. To alleviate these shortcomings, dataset distillation~(DD), also known as dataset condensation (DC), was introduced and has recently attracted much research attention in the community. Given an original dataset, DD aims to derive a much smaller dataset containing synthetic samples, based on which the trained models yield performance comparable with those trained on the original dataset. In this paper, we give a comprehensive review and summary of recent advances in DD and its application. We first introduce the task formally and propose an overall algorithmic framework followed by all existing DD methods. Next, we provide a systematic taxonomy of current methodologies in this area, and discuss their theoretical interconnections. We also present current challenges in DD through extensive experiments and envision possible directions for future works.Comment: 23 pages, 168 references, 8 figures, under revie

DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation

One key challenge of exemplar-guided image generation lies in establishing fine-grained correspondences between input and guided images. Prior approaches, despite the promising results, have relied on either estimating dense attention to compute per-point matching, which is limited to only coarse scales due to the quadratic memory cost, or fixing the number of correspondences to achieve linear complexity, which lacks flexibility. In this paper, we propose a dynamic sparse attention based Transformer model, termed Dynamic Sparse Transformer (DynaST), to achieve fine-level matching with favorable efficiency. The heart of our approach is a novel dynamic-attention unit, dedicated to covering the variation on the optimal number of tokens one position should focus on. Specifically, DynaST leverages the multi-layer nature of Transformer structure, and performs the dynamic attention scheme in a cascaded manner to refine matching results and synthesize visually-pleasing outputs. In addition, we introduce a unified training objective for DynaST, making it a versatile reference-based image translation framework for both supervised and unsupervised scenarios. Extensive experiments on three applications, pose-guided person image generation, edge-based face synthesis, and undistorted image style transfer, demonstrate that DynaST achieves superior performance in local details, outperforming the state of the art while reducing the computational cost significantly. Our code is available at https://github.com/Huage001/DynaSTComment: ECCV 202

Modeling Link-level Road Traffic Resilience to Extreme Weather Events Using Crowdsourced Data

Climate changes lead to more frequent and intense weather events, posing escalating risks to road traffic. Crowdsourced data offer new opportunities to monitor and investigate changes in road traffic flow during extreme weather. This study utilizes diverse crowdsourced data from mobile devices and the community-driven navigation app, Waze, to examine the impact of three weather events (i.e., floods, winter storms, and fog) on road traffic. Three metrics, speed change, event duration, and area under the curve (AUC), are employed to assess link-level traffic change and recovery. In addition, a user's perceived severity is computed to evaluate link-level weather impact based on crowdsourced reports. This study evaluates a range of new data sources, and provides insights into the resilience of road traffic to extreme weather, which are crucial for disaster preparedness, response, and recovery in road transportation systems

Castration modulates singing patterns and electrophysiological properties of RA projection neurons in adult male zebra finches

Castration can change levels of plasma testosterone. Androgens such as testosterone play an important role in stabilizing birdsong. The robust nucleus of the arcopallium (RA) is an important premotor nucleus critical for singing. In this study, we investigated the effect of castration on singing patterns and electrophysiological properties of projection neurons (PNs) in the RA of adult male zebra finches. Adult male zebra finches were castrated and the changes in bird song assessed. We also recorded the electrophysiological changes from RA PNs using patch clamp recording. We found that the plasma levels of testosterone were significantly decreased, song syllable’s entropy was increased and the similarity of motif was decreased after castration. Spontaneous and evoked firing rates, membrane time constants, and membrane capacitance of RA PNs in the castration group were lower than those of the control and the sham groups. Afterhyperpolarization AHP time to peak of spontaneous action potential (AP) was prolonged after castration.These findings suggest that castration decreases song stereotypy and excitability of RA PNs in male zebra finches

A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models

This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: (1) the new search direction possesses not only a sufficient descent property but also a trust region feature; (2) the presented algorithm has global convergence for nonconvex functions; (3) the numerical experiment showed that the new algorithm is more effective than similar algorithms

Comparison of Fatty Acid Composition, Phytochemical Profiles and Antioxidant Activities in Four Flax (Linum usitatissimum L.) Varieties

Abstract The present study was intendant to evaluate variations among flaxseed varities in terms of fatty acid composition, phytochemical profiles, and antioxidant activities determined by oxygen radical absorbance capacity (ORAC), 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferrous ion reducing antioxidant power (FRAP) assays. Significant variations in the fatty acid composition, phenolic acids and lignan were observed in flaxseed varieties from different countries. Among these flaxseed verities, the unsaturated fatty acids accounted over four fifths of total fatty acid contents. The highest ratio of linolenic acid of total fatty acid was observed in USPEA, whereas the lowest one was found in Yexiao. USPEA showed the most contents of total phenolics, as well as flaxseed lignans. In general, total phenolics appeared to be the main contributors in the antioxidant capacity of flaxseed, which presented significant positive correlation. Our study revealed that both cultivar and origin of seeds significantly affect fatty acid composition, phenolic acids, lignans and subsequent antioxidant activities in flaxseed. The results provide new aspects of breeding resources of flaxseed cultivars by presenting their quality specification and possible commercial value

Dopamine modulates synaptic transmission in the premotor nuclei of songbirds

Songbirds, such as zebra finches, contribute to explore behaviors underlying neural activities. Birdsong is controlled by the song system. The robust nucleus of the arcopallium (RA) is a key nucleus for producing birdsong in the song system. The RA receives dopaminergic （DArgic） inputs from the midbrain, however, the function of these inputs involved excitatory synaptic transmission is still unclear. Excitatory synaptic transmission is critical in the signal integration activities of the brain. We examined the effects of dopamine (DA) on excitatory synaptic transmission of the projection neurons in the RA of adult male zebra finches, using whole-cell recording technique. We found that DA (100 μM) decreases the frequency of spontaneous and miniature excitatory postsynaptic currents (sEPSCs/mEPSCs). In our further study, these effects of DA were reversed by the D1-like dopamine receptor (D1R) antagonist and stimulated by a D1R agonist. However, a D2-like dopamine receptor (D2R) has no influence on the effects of DA. These results demonstrate that DA can inhibit excitatory synaptic transmission mainly via activation of D1R in adult male zebra finches. PeerJ PrePrints | https://doi.org/10.7287/peerj.preprints.1563v1 | CC-BY 4.0 Open Access