715 research outputs found
On Searching a Table Consistent with Division Poset
Suppose is a partially ordered set with the partial order
defined by divisibility, that is, for any two distinct elements
satisfying divides , . A table of
distinct real numbers is said to be \emph{consistent} with , provided for
any two distinct elements satisfying divides ,
. Given an real number , we want to determine whether ,
by comparing with as few entries of as possible. In this paper we
investigate the complexity , measured in the number of comparisons, of
the above search problem. We present a search
algorithm for and prove a lower bound on
by using an adversary argument.Comment: 16 pages, no figure; same results, representation improved, add
reference
Turbo-like Iterative Multi-user Receiver Design for 5G Non-orthogonal Multiple Access
Non-orthogonal multiple access (NoMA) as an efficient way of radio resource
sharing has been identified as a promising technology in 5G to help improving
system capacity, user connectivity, and service latency in 5G communications.
This paper provides a brief overview of the progress of NoMA transceiver study
in 3GPP, with special focus on the design of turbo-like iterative multi-user
(MU) receivers. There are various types of MU receivers depending on the
combinations of MU detectors and interference cancellation (IC) schemes.
Link-level simulations show that expectation propagation algorithm (EPA) with
hybrid parallel interference cancellation (PIC) is a promising MU receiver,
which can achieve fast convergence and similar performance as message passing
algorithm (MPA) with much lower complexity.Comment: Accepted by IEEE 88th Vehicular Technology Conference (IEEE VTC-2018
Fall), 5 pages, 6 figure
A Universal Receiver for Uplink NOMA Systems
Given its capability in efficient radio resource sharing, non-orthogonal
multiple access (NOMA) has been identified as a promising technology in 5G to
improve the system capacity, user connectivity, and scheduling latency. A dozen
of uplink NOMA schemes have been proposed recently and this paper considers the
design of a universal receiver suitable for all potential designs of NOMA
schemes. Firstly, a general turbo-like iterative receiver structure is
introduced, under which, a universal expectation propagation algorithm (EPA)
detector with hybrid parallel interference cancellation (PIC) is proposed (EPA
in short). Link-level simulations show that the proposed EPA receiver can
achieve superior block error rate (BLER) performance with implementation
friendly complexity and fast convergence, and is always better than the
traditional codeword level MMSE-PIC receiver for various kinds of NOMA schemes.Comment: This paper has been accepted by IEEE/CIC International Conference on
Communications in China (ICCC 2018). 5 pages, 4 figure
Nonequilibrium spin injection in monolayer black phosphorus
Monolayer black phosphorus (MBP) is an interesting emerging electronic
material with a direct band gap and relatively high carrier mobility. In this
work we report a theoretical investigation of nonequilibrium spin injection and
spin-polarized quantum transport in MBP from ferromagnetic Ni contacts, in
two-dimensional magnetic tunneling structures. We investigate physical
properties such as the spin injection efficiency, the tunnel magnetoresistance
ratio, spin-polarized currents, charge currents and transmission coefficients
as a function of external bias voltage, for two different device contact
structures where MBP is contacted by Ni(111) and by Ni(100). While both
structures are predicted to give respectable spin-polarized quantum transport,
the Ni(100)/MBP/Ni(100) trilayer has the superior properties where the spin
injection and magnetoresistance ratio maintains almost a constant value against
the bias voltage. The nonequilibrium quantum transport phenomenon is understood
by analyzing the transmission spectrum at nonequilibrium.Comment: 6 pages, 6 figure
DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection
Fully convolutional detectors discard the one-to-many assignment and adopt a
one-to-one assigning strategy to achieve end-to-end detection but suffer from
the slow convergence issue. In this paper, we revisit these two assignment
methods and find that bringing one-to-many assignment back to end-to-end fully
convolutional detectors helps with model convergence. Based on this
observation, we propose {\em \textbf{D}ual \textbf{A}ssignment} for end-to-end
fully convolutional de\textbf{TE}ction (DATE). Our method constructs two
branches with one-to-many and one-to-one assignment during training and speeds
up the convergence of the one-to-one assignment branch by providing more
supervision signals. DATE only uses the branch with the one-to-one matching
strategy for model inference, which doesn't bring inference overhead.
Experimental results show that Dual Assignment gives nontrivial improvements
and speeds up model convergence upon OneNet and DeFCN. Code:
https://github.com/YiqunChen1999/date
Testing for a difference in means of a single feature after clustering
For many applications, it is critical to interpret and validate groups of
observations obtained via clustering. A common validation approach involves
testing differences in feature means between observations in two estimated
clusters. In this setting, classical hypothesis tests lead to an inflated Type
I error rate. To overcome this problem, we propose a new test for the
difference in means in a single feature between a pair of clusters obtained
using hierarchical or -means clustering. The test based on the proposed
-value controls the selective Type I error rate in finite samples and can be
efficiently computed. We further illustrate the validity and power of our
proposal in simulation and demonstrate its use on single-cell RNA-sequencing
data
What if Social Bots Be My Friends? Estimating Causal Effect of Social Bots Using Counterfactual Graph Learning
Essays on Macroeconomic Trends and Cycles
This dissertation describes two studies on macroeconomic trends and cycles. The first chapter studies the impact of Information Technology (IT) on the U.S. labor market. Over the past 30 years, employment and income shares of routine-intensive occupations have declined significantly relative to nonroutine occupations, and the overall U.S. labor income share has declined relative to capital. Furthermore, the decline of routine employment has been largely concentrated during recessions and ensuing recoveries. I build a model of unbalanced growth to assess the role of computerization and IT in driving these labor market trends and cycles. I augment a neoclassical growth model with exogenous IT progress as a form of Routine-Biased Technological Change (RBTC). I show analytically that RBTC causes the overall labor income share to follow a U-shaped time path, as the monotonic decline of routine labor share is increasingly offset by the monotonic rise of nonroutine labor share and the elasticity of substitution between the overall labor and capital declines under IT progress. Quantitatively, the model explains nearly all the divergence between routine and nonroutine labor in the period 1986-2014, as well as the mild decline of the overall labor share between 1986 and the early 2000s. However, the model with IT progress alone cannot explain the accelerated decline of labor income share after the early 2000s, suggesting that other factors, such as globalization, may have played a larger role in this period. Lastly, when nonconvex labor adjustment costs are present, the model generates a stepwise decline in routine labor hours, qualitatively consistent with the data. The timing of these trend adjustments can be significantly affected by aggregate productivity shocks and concentrated in recessions.
The second chapter studies the implications of loss aversion on the business cycle dynamics of aggregate consumption and labor hours. Loss aversion refers to the fact that people are distinctively more sensitive to losses than to gains. Loss averse agents are very risk averse around the reference point and exhibit asymmetric responses to positive and negative income shocks. In an otherwise standard Real Business Cycle (RBC) model, I study loss aversion in both consumption alone and consumption-and-leisure together. My results indicate that how loss aversion affects business cycle dynamics depends critically on the nature of the reference point. If, for example, the reference point is status quo, loss aversion dramatically lowers the effective inter-temporal rate of substitution and induces excessive consumption smoothing. In contrast, if the reference point is fixed at a constant level, loss aversion generates a flat region in the decision rules and asymmetric impulse responses to technology shocks. Under a reasonable parametrization, loss aversion has the potential to generate asymmetric business cycles with deeper and more prolonged recessions
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