Dataset Distillation with Convexified Implicit Gradients

We propose a new dataset distillation algorithm using reparameterization and convexification of implicit gradients (RCIG), that substantially improves the state-of-the-art. To this end, we first formulate dataset distillation as a bi-level optimization problem. Then, we show how implicit gradients can be effectively used to compute meta-gradient updates. We further equip the algorithm with a convexified approximation that corresponds to learning on top of a frozen finite-width neural tangent kernel. Finally, we improve bias in implicit gradients by parameterizing the neural network to enable analytical computation of final-layer parameters given the body parameters. RCIG establishes the new state-of-the-art on a diverse series of dataset distillation tasks. Notably, with one image per class, on resized ImageNet, RCIG sees on average a 108% improvement over the previous state-of-the-art distillation algorithm. Similarly, we observed a 66% gain over SOTA on Tiny-ImageNet and 37% on CIFAR-100

Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation

Modern deep learning requires large volumes of data, which could contain sensitive or private information that cannot be leaked. Recent work has shown for homogeneous neural networks a large portion of this training data could be reconstructed with only access to the trained network parameters. While the attack was shown to work empirically, there exists little formal understanding of its effective regime which datapoints are susceptible to reconstruction. In this work, we first build a stronger version of the dataset reconstruction attack and show how it can provably recover the \emph{entire training set} in the infinite width regime. We then empirically study the characteristics of this attack on two-layer networks and reveal that its success heavily depends on deviations from the frozen infinite-width Neural Tangent Kernel limit. Next, we study the nature of easily-reconstructed images. We show that both theoretically and empirically, reconstructed images tend to "outliers" in the dataset, and that these reconstruction attacks can be used for \textit{dataset distillation}, that is, we can retrain on reconstructed images and obtain high predictive accuracy

Mid-IR heterogeneous silicon photonics

In this paper we discuss silicon-based photonic integrated circuit technology for applications beyond the telecommunication wavelength range. Silicon-on-insulator and germanium-on-silicon passive waveguide circuits are described, as well as the integration of III-V semiconductors, IV-VI colloidal nanoparticle films and GeSn alloys on these circuits for increasing the functionality. The strong nonlinearity of silicon combined with the low nonlinear absorption in the mid-infrared is exploited to generate picosecond pulse based supercontinuum sources and optical parametric oscillators that can be used as spectroscopic sensor sources

Nanocrystalline hydroxyapatite and zinc-doped hydroxyapatite as carrier material for controlled delivery of ciprofloxacin

In bone disorders infections are common. The concentration of majority of antibiotics is very low in the bone tissue. A high local dose can be obtained from the ciprofloxacin-loaded hydroxyapatite nanoparticles. The present study is aimed at developing the use of hydroxyapatite and zinc-doped hydroxyapatite nanoparticles as a carrier for ciprofloxacin drug delivery system. The ciprofloxacin-loaded hydroxyapatite and zinc-doped hydroxyapatite have a good antibacterial activity against Pseudomonas aeruginosa and Staphylococcus aureus. Hydroxyapatite and zinc-doped hydroxyapatite were prepared and characterized using X-ray diffraction, Transmission electron microscopy and inductively coupled plasma optical emission spectrometry. They were loaded with ciprofloxacin using optimized drug loading parameters. Drug loading, in vitro drug release and antimicrobial activity were analyzed. The influence of zinc on the controlled release of ciprofloxacin was analyzed. The results show that the presence of zinc increases the drug release percentage and that the drug was released in a controlled manner

The Youngest Victims: Children and Youth Affected by War

In 1989, the United Nation Convention on the Rights of the Child declared, “[state parties] shall take all feasible measures to ensure protection and care of children who are affected by an armed conflict.” In addition to attempting to secure the welfare of children in armed conflict, the Convention went on to ban the recruitment and deployment of children during armed conflict. Despite the vast majority of sovereign nations signing and ratifying this agreement, this treaty, unfortunately, has not prevented children and youth from witnessing, becoming victims of, or participating in political, ethnic, religious, and cultural violence across the past three decades. This chapter offers an “ecological perspective” on the psychosocial consequences of exposure to the trauma of war-related violence and social disruption

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi