92,941 research outputs found
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels
One important assumption underlying common classification models is the
stationarity of the data. However, in real-world streaming applications, the
data concept indicated by the joint distribution of feature and label is not
stationary but drifting over time. Concept drift detection aims to detect such
drifts and adapt the model so as to mitigate any deterioration in the model's
predictive performance. Unfortunately, most existing concept drift detection
methods rely on a strong and over-optimistic condition that the true labels are
available immediately for all already classified instances. In this paper, a
novel Hierarchical Hypothesis Testing framework with Request-and-Reverify
strategy is developed to detect concept drifts by requesting labels only when
necessary. Two methods, namely Hierarchical Hypothesis Testing with
Classification Uncertainty (HHT-CU) and Hierarchical Hypothesis Testing with
Attribute-wise "Goodness-of-fit" (HHT-AG), are proposed respectively under the
novel framework. In experiments with benchmark datasets, our methods
demonstrate overwhelming advantages over state-of-the-art unsupervised drift
detectors. More importantly, our methods even outperform DDM (the widely used
supervised drift detector) when we use significantly fewer labels.Comment: Published as a conference paper at IJCAI 201
Hydrogen as a Source of Flux Noise in SQUIDs
Superconducting qubits are hampered by flux noise produced by surface spins
from a variety of microscopic sources. Recent experiments indicated that
hydrogen (H) atoms may be one of those sources. Using density functional theory
calculations, we report that H atoms either embedded in, or adsorbed on, an
a-Al2O3(0001) surface have sizeable spin moments ranging from 0.81 to 0.87 uB
with energy barriers for spin reorientation as low as ~10 mK. Furthermore, H
adatoms on the surface attract gas molecules such as O2, producing new spin
sources. We propose coating the surface with graphene to eliminate H-induced
surface spins and to protect the surface from other adsorbates.Comment: 12 pages, 4 figure
Effect of weak measurement on entanglement distribution over noisy channels
Being able to implement effective entanglement distribution in noisy
environments is a key step towards practical quantum communication, and
long-term efforts have been made on the development of it. Recently, it has
been found that the null-result weak measurement (NRWM) can be used to enhance
probabilistically the entanglement of a single copy of amplitude-damped
entangled state. This paper investigates remote distributions of bipartite and
multipartite entangled states in the amplitudedamping environment by combining
NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has
no positive effect on the distribution of bipartite maximally entangled states
and multipartite Greenberger-Horne-Zeilinger states, although it is able to
increase the amount of entanglement of each source state (noisy entangled
state) of EDPs with a certain probability. However, we find that the NRWM would
contribute to remote distributions of multipartite W states. We demonstrate
that the NRWM can not only reduce the fidelity thresholds for distillability of
decohered W states, but also raise the distillation efficiencies of W states.
Our results suggest a new idea for quantifying the ability of a local filtering
operation in protecting entanglement from decoherence.Comment: 15 pages, 9 figures. Minor revision has been mad
Dynamic Provable Data Possession Protocols with Public Verifiability and Data Privacy
Cloud storage services have become accessible and used by everyone.
Nevertheless, stored data are dependable on the behavior of the cloud servers,
and losses and damages often occur. One solution is to regularly audit the
cloud servers in order to check the integrity of the stored data. The Dynamic
Provable Data Possession scheme with Public Verifiability and Data Privacy
presented in ACISP'15 is a straightforward design of such solution. However,
this scheme is threatened by several attacks. In this paper, we carefully
recall the definition of this scheme as well as explain how its security is
dramatically menaced. Moreover, we proposed two new constructions for Dynamic
Provable Data Possession scheme with Public Verifiability and Data Privacy
based on the scheme presented in ACISP'15, one using Index Hash Tables and one
based on Merkle Hash Trees. We show that the two schemes are secure and
privacy-preserving in the random oracle model.Comment: ISPEC 201
Design of a 2.4 GHz High-Performance Up-Conversion Mixer with Current Mirror Topology
In this paper, a low voltage low power up-conversion mixer, designed in a Chartered 0.18 μm RFCMOS technology, is proposed to realize the transmitter front-end in the frequency band of 2.4 GHz. The up-conversion mixer uses the current mirror topology and current-bleeding technique in both the driver and switching stages with a simple degeneration resistor. The proposed mixer converts an input of 100 MHz intermediate frequency (IF) signal to an output of 2.4 GHz radio frequency (RF) signal, with a local oscillator (LO) power of 2 dBm at 2.3 GHz. A comparison with conventional CMOS up-conversion mixer shows that this mixer has advantages of low voltage, low power consumption and high-performance. The post-layout simulation results demonstrate that at 2.4 GHz, the circuit has a conversion gain of 7.1 dB, an input-referred third-order intercept point (IIP3) of 7.3 dBm and a noise figure of 11.9 dB, while drawing only 3.8 mA for the mixer core under a supply voltage of 1.2 V. The chip area including testing pads is only 0.62×0.65 mm2
Log-Harnack Inequality for Stochastic Differential Equations in Hilbert Spaces and its Consequences
A logarithmic type Harnack inequality is established for the semigroup of
solutions to a stochastic differential equation in Hilbert spaces with
non-additive noise. As applications, the strong Feller property as well as the
entropy-cost inequality for the semigroup are derived with respect to the
corresponding distance (cost function)
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