When do Models Generalize? A Perspective from Data-Algorithm Compatibility

One of the major open problems in machine learning is to characterize generalization in the overparameterized regime, where most traditional generalization bounds become inconsistent (Nagarajan and Kolter, 2019). In many scenarios, their failure can be attributed to obscuring the crucial interplay between the training algorithm and the underlying data distribution. To address this issue, we propose a concept named compatibility, which quantitatively characterizes generalization in a both data-relevant and algorithm-relevant manner. By considering the entire training trajectory and focusing on early-stopping iterates, compatibility exploits the data and the algorithm information and is therefore a more suitable notion for generalization. We validate this by theoretically studying compatibility under the setting of solving overparameterized linear regression with gradient descent. Specifically, we perform a data-dependent trajectory analysis and derive a sufficient condition for compatibility in such a setting. Our theoretical results demonstrate that in the sense of compatibility, generalization holds with significantly weaker restrictions on the problem instance than the previous last iterate analysis

Connexin43 hemichannels contributes to the disassembly of cell junctions through modulation of intracellular oxidative status

AbstractConnexin (Cx) hemichannels regulate many cellular processes with little information available regarding their mechanisms. Given that many pathological factors that activate hemichannels also disrupts the integrity of cellular junctions, we speculated a potential participation of hemichannels in the regulation of cell junctions. Here we tested this hypothesis. Exposure of renal tubular epithelial cells to Ca2+-free medium led to disassembly of tight and adherens junctions, as indicated by the reduced level of ZO-1 and cadherin, disorganization of F-actin, and severe drop in transepithelial electric resistance. These changes were preceded by an activation of Cx43 hemichannels, as revealed by extracellular efflux of ATP and intracellular influx of Lucifer Yellow. Inhibition of hemichannels with chemical inhibitors or Cx43 siRNA greatly attenuated the disassembly of cell junctions. Further analysis using fetal fibroblasts derived from Cx43 wide-type (Cx43+/+), heterozygous (Cx43+/-) and knockout (Cx43-/-) littermates showed that Cx43-positive cells (Cx43+/+) exhibited more dramatic changes in cell shape, F-actin, and cadherin in response to Ca2+ depletion, as compared to Cx43-null cells (Cx43-/-). Consistently, these cells had higher level of protein carbonyl modification and phosphorylation, and much stronger activation of P38 and JNK. Hemichannel opening led to extracellular loss of the major antioxidant glutathione (GSH). Supplement of cells with exogenous GSH or inhibition of oxidative sensitive kinases largely prevented the above-mentioned changes. Taken together, our study indicates that Cx43 hemichannels promote the disassembly of cell junctions through regulation of intracellular oxidative status

Towards Relating Fragile-To-Strong Transition to Fragile Glass

Glass formers are in general classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are however notable exceptions such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong respectively at high and low temperatures. In this work, the FTS transition is studied using a distinguishable-particle lattice model previously demonstrated to be capable of simulating both strong and fragile glasses [Phys. Rev. Lett. 125, 265703 (2020)]. Starting with a bimodal pair-interaction distribution appropriate for fragile glasses, we show that by narrowing down the energy dispersion in the low-energy component of the distribution, a FTS transition is observed. The transition occurs at a temperature at which the stretching exponent of the relaxation is minimized, in agreement with previous molecular dynamics simulations

Dirac-Surface-State Modulated Spin Dynamics in a Ferrimagnetic Insulator at Room Temperature

This work demonstrates dramatically modified spin dynamics of magnetic insulator (MI) by the spin-momentum locked Dirac surface states of the adjacent topological insulator (TI) which can be harnessed for spintronic applications. As the Bi-concentration x is systematically tuned in 5 nm thick (BixSb1-x)2Te3 TI film, the weight of the surface relative to bulk states peaks at x = 0.32 when the chemical potential approaches the Dirac point. At this concentration, the Gilbert damping constant of the precessing magnetization in 10 nm thick Y3Fe5O12 MI film in the MI/TI heterostructures is enhanced by an order of magnitude, the largest among all concentrations. In addition, the MI acquires additional strong magnetic anisotropy that favors the in-plane orientation with similar Bi-concentration dependence. These extraordinary effects of the Dirac surface states distinguish TI from other materials such as heavy metals in modulating spin dynamics of the neighboring magnetic layer