arXiv subjects

Yifei Wang

Publications and source records attributed to Yifei Wang.

226 records · Page 13Linked to original sources

arXiv2020

Decoder-free Robustness Disentanglement without (Additional) Supervision

Adversarial Training (AT) is proposed to alleviate the adversarial vulnerability of machine learning models by extracting only robust features from the input, which, however, inevitably leads to severe accuracy reduction as it discards the non-robust yet useful features. This motivates us to preserve both robust and non-robust features and separate them with disentangled representation learning. Our proposed Adversarial Asymmetric Training (AAT) algorithm can reliably disentangle robust and non-robust representations without additional supervision on robustness. Empirical results show our method does not only successfully preserve accuracy by combining two representations, but also achieve much better disentanglement than previous work.

stat.ML↗

arXiv2020

Experimental validation of a phase-field model to predict coarsening dynamics of lipid domains in multicomponent membranes

Membrane phase-separation is a mechanism that biological membranes often use to locally concentrate specific lipid species in order to organize diverse membrane processes. Phase separation has also been explored as a tool for the design of liposomes with heterogeneous and spatially organized surfaces. These "patchy" liposomes are promising platforms for delivery purposes, however their design and optimization through experimentation can be expensive and time-consuming. We developed a computationally efficient method based on the surface Cahn-Hilliard phase-field model to complement experimental investigations in the design of patchy liposomes. The method relies on thermodynamic considerations to set the initial state for numerical simulations. We show that our computational approach delivers not only qualitative pictures, but also accurate quantitative information about the dynamics of the membrane organization. In particular, the computational and experimental results are in excellent agreement in terms of raft area fraction, total raft perimeter over time and total number of rafts over time for two different membrane compositions (DOPC:DPPC with a 2:1 molar ratio with 20% Chol and DOPC:DPPC with a 3:1 molar ratio with 20% Chol). Thus, the computational phase-field model informed by experiments has a considerable potential to assist in the design of liposomes with spatially organized surfaces, thereby containing the cost and time required by the design process.

physics.comp-ph↗

arXiv2019

Interaction Mechanism and Response of Tidal Effect on the Shallow Geology of Europa

Europa has been conf irmed to have a multilayered structure and complex geological condition in last two decades whose detail and cause of formation remains unclear.In this work,we start from analyzing the mechanism of tidal ef fect on satellite's surface and discuss if interaction like tidal locking and orbital resonance play an important role in tidal ef fect including heating,underground convection and eruption.During discussion we propose the main factors affecting Europa's tidal heat and the formation mechanism of typical shallow geological features,and provide theoretical support for further exploration.

astro-ph.EP↗

arXiv2019

Regularized Non-negative Spectral Embedding for Clustering

Spectral Clustering is a popular technique to split data points into groups, especially for complex datasets. The algorithms in the Spectral Clustering family typically consist of multiple separate stages (such as similarity matrix construction, low-dimensional embedding, and K-Means clustering as post processing), which may lead to sub-optimal results because of the possible mismatch between different stages. In this paper, we propose an end-to-end single-stage learning method to clustering called Regularized Non-negative Spectral Embedding (RNSE) which extends Spectral Clustering with the adaptive learning of similarity matrix and meanwhile utilizes non-negative constraints to facilitate one-step clustering (directly from data points to clustering labels). Two well-founded methods, successive alternating projection and strategic multiplicative update, are employed to work out the quite challenging optimization problems in RNSE. Extensive experiments on both synthetic and real-world datasets demonstrate RNSE superior clustering performance to some state-of-the-art competitors.

cs.LG↗

arXiv2019

The Search direction Correction makes first-order methods faster

The so-called fast inertial relaxation engine is a first-order method for unconstrained smooth optimization problems. It updates the search direction by a linear combination of the past search direction, the current gradient and the normalized gradient direction. We explore more general combination rules and call this generalized technique as the search direction correction (SDC). SDC is extended to composite and stochastic optimization problems as well. Deriving from a second-order ODE, we propose a fast inertial search direction correction (FISC) algorithm as an example of methods with SDC. We prove the $\mathcal{O}(k^{-2})$ convergence rate of FISC for convex optimization problems. Numerical results on sparse optimization, logistic regression as well as deep learning demonstrate that our proposed methods are quite competitive to other state-of-the-art first-order algorithms.

math.OC↗

arXiv2017

Deep Domain Adaptation by Geodesic Distance Minimization

In this paper, we propose a new approach called Deep LogCORAL for unsupervised visual domain adaptation. Our work builds on the recently proposed Deep CORAL method, which proposed to train a convolutional neural network and simultaneously minimize the Euclidean distance of convariance matrices between the source and target domains. We propose to use the Riemannian distance, approximated by Log-Euclidean distance, to replace the naive Euclidean distance in Deep CORAL. We also consider first-order information, and minimize the distance of mean vectors between two domains. We build an end-to-end model, in which we minimize both the classification loss, and the domain difference based on the first and second order information between two domains. Our experiments on the benchmark Office dataset demonstrate the improvements of our newly proposed Deep LogCORAL approach over the Deep CORAL method, as well as further improvement when optimizing both orders of information.

cs.CV↗

arXiv2016

Virtual Breakdown Mechanism: Field-Driven Splitting of Pure Water for Hydrogen Production

Due to the low conductivity of pure water, using an electrolyte is common for achieving efficient water electrolysis. In this paper, we have broken through this common sense by using deep-sub-Debye-length nanogap electrochemical cells for the electrolysis of pure water. At such nanometer scale, the field-driven pure water splitting exhibits a completely different mechanism from the macrosystem. We have named this process 'virtual breakdown mechanism' that results in a series of fundamental changes and more than 10^5-fold enhancement of the equivalent conductivity of pure water. This fundamental discovery has been theoretically discussed in this paper and experimentally demonstrated in a group of electrochemical cells with nanogaps between two electrodes down to 37 nm. Based on our nanogap electrochemical cells, the electrolysis current from pure water is comparable to or even larger than the current from 1 mol/L sodium hydroxide solution, indicating the high-efficiency of pure water splitting as a potential for on-demand hydrogen production.

physics.chem-ph↗

arXiv2016

Immense magnetic response of exciplex light emission due to correlated spin-charge dynamics

As carriers slowly move through a disordered energy landscape in organic semiconductors, tiny spatial variations in spin dynamics relieve spin blocking at transport bottlenecks or in the electron-hole recombination process that produces light. Large room-temperature magnetic-field effects (MFE) ensue in the conductivity and luminescence. Sources of variable spin dynamics generate much larger MFE if their spatial structure is correlated on the nanoscale with the energetic sites governing conductivity or luminescence such as in co-evaporated organic blends within which the electron resides on one molecule and the hole on the other (an exciplex). Here we show that exciplex recombination in blends exhibiting thermally-activated delayed fluorescence (TADF) produces MFE in excess of 60% at room temperature. In addition, effects greater than 4000% can be achieved by tuning the device's current-voltage response curve by device conditioning. These immense MFEs are both the largest reported values for their device type at room temperature. Our theory traces this MFE and its unusual temperature dependence to changes in spin mixing between triplet exciplexes and light-emitting singlet exciplexes. In contrast, spin mixing of excitons is energetically suppressed, and thus spin mixing produces comparatively weaker MFE in materials emitting light from excitons by affecting the precursor pairs. Demonstration of immense MFE in common organic blends provides a flexible and inexpensive pathway towards magnetic functionality and field sensitivity in current organic devices without patterning the constituent materials on the nanoscale. Magnetic fields increase the power efficiency of unconditioned devices by 30% at room temperature, also showing that magnetic fields may increase the efficiency of the TADF process.

cond-mat.mes-hall↗

arXiv2015

High-Responsivity Graphene-Boron Nitride Photodetector and Autocorrelator in a Silicon Photonic Integrated Circuit

Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal-oxide-semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cut-off at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we conclude that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron-phonon supercollision cooling. This nonlinear photoresponse enables optical on-chip autocorrelation measurements with picosecond-scale timing resolution and exceptionally low peak powers.

physics.optics↗

arXiv2014

A Systematic Security Evaluation of Android's Multi-User Framework

Like many desktop operating systems in the 1990s, Android is now in the process of including support for multi-user scenarios. Because these scenarios introduce new threats to the system, we should have an understanding of how well the system design addresses them. Since the security implications of multi-user support are truly pervasive, we developed a systematic approach to studying the system and identifying problems. Unlike other approaches that focus on specific attacks or threat models, ours systematically identifies critical places where access controls are not present or do not properly identify the subject and object of a decision. Finding these places gives us insight into hypothetical attacks that could result, and allows us to design specific experiments to test our hypothesis. Following an overview of the new features and their implementation, we describe our methodology, present a partial list of our most interesting hypotheses, and describe the experiments we used to test them. Our findings indicate that the current system only partially addresses the new threats, leaving the door open to a number of significant vulnerabilities and privacy issues. Our findings span a spectrum of root causes, from simple oversights, all the way to major system design problems. We conclude that there is still a long way to go before the system can be used in anything more than the most casual of sharing environments.

cs.CR↗