Search

In recent years, rumor news has been generated by humans as well as robots inorder to attract readership, influence opinions, and increase internet clickrevenue. Its detrimental effects have become a worldwide phenomenon, leading toconfusion over facts and causing mistrust about media reports...

This paper studies the revenue of simple mechanisms in settings where athird-party data provider is present. When no data provider is present, it isknown that simple mechanisms achieve a constant fraction of the revenue ofoptimal mechanisms. The results in this paper demonstrate that this is...

Multi-server coded caching, which can further reduce the amount oftransmission by means of the collaboration among these servers in the wirelessnetwork during the peak traffic times, can be seen everywhere in our life. Thisamount is called rate. The three servers setting (two data servers and...

Single image rain streak removal is an extremely challenging problem due tothe presence of non-uniform rain densities in images. We present a noveldensity-aware multi-stream densely connected convolutional neural network-basedalgorithm, called DID-MDN, for joint rain density estimation and de...

In this paper, we propose a method to cluster multiple intersected manifolds.The algorithm chooses several landmark nodes randomly and then checks whetherthere is an angle constrained path between each landmark node and every othernode in the neighborhood graph. When the points lie on different...

Mixture-of-Experts (MoE) is a widely popular neural network architecture andis a basic building block of highly successful modern neural networks, forexample, Gated Recurrent Units (GRU) and Attention networks. However, despitethe empirical success, finding an efficient and provably consistent...

Techniques for multi-lingual and cross-lingual speech recognition can help inlow resource scenarios, to bootstrap systems and enable analysis of newlanguages and domains. End-to-end approaches, in particular sequence-basedtechniques, are attractive because of their simplicity and elegance. While...

Employing deep learning-based approaches for fine-grained facial expressionanalysis, such as those involving the estimation of Action Unit (AU)intensities, is difficult due to the lack of a large-scale dataset of realfaces with sufficiently diverse AU labels for training. In this paper, weconsider...

We discuss several uses of blockchain (and, more generally, distributedledger) technologies outside of cryptocurrencies with a pragmatic view. Wemostly focus on three areas: the role of coin economies for what we refer to asdata malls (specialized data marketplaces); data provenance (a...

We study the problem of computing the $p\rightarrow q$ norm of a matrix $A\in R^{m \times n}$, defined as \[ \|A\|_{p\rightarrow q} ~:=~ \max_{x \,\in\,R^n \setminus \{0\}} \frac{\|Ax\|_q}{\|x\|_p} \] This problem generalizes thespectral norm of a matrix ($p=q=2$) and the Grothendieck problem ($p=...

In the large-scale multiclass setting, assigning labels often consists ofanswering multiple questions to drill down through a hierarchy of classes.Here, the labor required per annotation scales with the number of questionsasked. We propose active learning with partial feedback. In this setup...

In today's data center, a diverse mix of throughput-sensitive long flows anddelay-sensitive short flows are commonly presented in shallow-bufferedswitches. Long flows could potentially block the transmission ofdelay-sensitive short flows, leading to degraded performance. Congestion canalso be caused...

Pebble games were originally formulated to study time-space tradeoffs incomputation, modeled by games played on directed acyclic graphs (DAGs). Closeconnections between pebbling and cryptography have been known for decades. Aseries of recent research starting with (Alwen and Serbinenko, STOC 2015)...

We introduce two-player games which build words over infinite alphabets, andwe study the problem of checking the existence of winning strategies. Thesegames are played by two players, who take turns in choosing valuations forvariables ranging over an infinite data domain, thus generatingmulti...

Learning compact binary codes for image retrieval problem using deep neuralnetworks has attracted increasing attention recently. However, training deephashing networks is challenging due to the binary constraints on the hashcodes, the similarity preserving properties, and the requirement for a...

In the weighted flow-time problem on a single machine, we are given a set ofn jobs, where each job has a processing requirement p_j, release date r_j andweight w_j. The goal is to find a preemptive schedule which minimizes the sumof weighted flow-time of jobs, where the flow-time of a job is the...

We consider the max-size popular matching problem in a roommates instance G =(V,E) with strict preference lists. A matching M is popular if there is nomatching M' in G such that the vertices that prefer M' to M outnumber thosethat prefer M to M'. We show it is NP-hard to compute a max-size...

In contrast to time series, graphical data is data indexed by the nodes andedges of a graph. Modern applications such as the internet, social networks,genomics and proteomics generate graphical data, often at large scale. Thelarge scale argues for the need to compress such data for storage...

Multi-view face synthesis from a single image is an ill-posed problem andoften suffers from serious appearance distortion. Producing photo-realistic andidentity preserving multi-view results is still a not well defined synthesisproblem. This paper proposes Load Balanced Generative Adversarial...

In recent years, geotagged social media has become popular as a novel sourcefor geographic knowledge discovery. Ground-level images and videos provide adifferent perspective than overhead imagery and can be applied to a range ofapplications such as land use mapping, activity detection, pollution...