236 research outputs found
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
A Benchmark for Structured Extractions from Complex Documents
Understanding visually-rich business documents to extract structured data and
automate business workflows has been receiving attention both in academia and
industry. Although recent multi-modal language models have achieved impressive
results, we find that existing benchmarks do not reflect the complexity of real
documents seen in industry. In this work, we identify the desiderata for a more
comprehensive benchmark and propose one we call Visually Rich Document
Understanding (VRDU). VRDU contains two datasets that represent several
challenges: rich schema including diverse data types as well as nested
entities, complex templates including tables and multi-column layouts, and
diversity of different layouts (templates) within a single document type. We
design few-shot and conventional experiment settings along with a carefully
designed matching algorithm to evaluate extraction results. We report the
performance of strong baselines and three observations: (1) generalizing to new
document templates is very challenging, (2) few-shot performance has a lot of
headroom, and (3) models struggle with nested fields such as line-items in an
invoice. We plan to open source the benchmark and the evaluation toolkit. We
hope this helps the community make progress on these challenging tasks in
extracting structured data from visually rich documents
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