OpenRaiser/Intern-Atlas huggingface dataset:
Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose
Venue: arXiv cs.CV 2016
Year: 2016

This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i) Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii) Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii) Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.
Adobe-MIT submission to the DSTC 4 Spoken Language Understanding pilot task
Venue: arXiv cs.CL 2016
Year: 2016

The Dialog State Tracking Challenge 4 (DSTC 4) proposes several pilot tasks. In this paper, we focus on the spoken language understanding pilot task, which consists of tagging a given utterance with speech acts and semantic slots. We compare different classifiers: the best system obtains 0.52 and 0.67 F1-scores on the test set for speech act recognition for the tourist and the guide respectively, and 0.52 F1-score for semantic tagging for both the guide and the tourist.
Unified Error Rates Analysis of MIMO Space-Time Block Codes over Generalized Shadowed κ-μ and η-μ Fading and AWGGN
Venue: arXiv cs.IT 2016
Year: 2016

This paper presents a novel unified performance analysis of Space-Time Block Codes (STBCs) operating in the Multiple Input Multiple Output (MIMO) network and subjected to generalized shadowed fading and noise scenarios. Specifically, we derive novel, simple and accurate average bit error rates (ABER) expressions for coherent modulation schemes in the generalized η-μ and shadowed κ-μ fading channels. The noise in the network is assumed to be modeled by the additive white generalized Gaussian noise (AWGGN), which encompasses the Laplacian and the Gaussian noise environments as special cases. The result obviates the need to re-derive the error rates for MIMO STBC systems under many multipath fading and noise models, while avoiding computationally-expensive expressions. Published results from the literature as well as numerical simulations corroborate the accuracy of our derived generalized expressions.
Problems With Evaluation of Word Embeddings Using Word Similarity Tasks
Venue: arXiv cs.CL 2016
Year: 2016

Lacking standardized extrinsic evaluation methods for vector representations of words, the NLP community has relied heavily on word similarity tasks as a proxy for intrinsic evaluation of word vectors. Word similarity evaluation, which correlates the distance between vectors and human judgments of semantic similarity is attractive, because it is computationally inexpensive and fast. In this paper we present several problems associated with the evaluation of word vectors on word similarity datasets, and summarize existing solutions. Our study suggests that the use of word similarity tasks for evaluation of word vectors is not sustainable and calls for further research on evaluation methods.
A Robust Zero-Calibration RF-based Localization System for Realistic Environments
Venue: arXiv cs.NI 2016
Year: 2016

Due to the noisy indoor radio propagation channel, Radio Frequency (RF)-based location determination systems usually require a tedious calibration phase to construct an RF fingerprint of the area of interest. This fingerprint varies with the used mobile device, changes of the transmit power of smart access points (APs), and dynamic changes in the environment; requiring re-calibration of the area of interest; which reduces the technology ease of use. In this paper, we present IncVoronoi: a novel system that can provide zero-calibration accurate RF-based indoor localization that works in realistic environments. The basic idea is that the relative relation between the received signal strength from two APs at a certain location reflects the relative distance from this location to the respective APs. Building on this, IncVoronoi incrementally reduces the user ambiguity region based on refining the Voronoi tessellation of the area of interest. IncVoronoi also includes a number of modules to efficiently run in realtime as well as to handle practical deployment issues including the noisy wireless environment, obstacles in the environment, heterogeneous devices hardware, and smart APs. We have deployed IncVoronoi on different Android phones using the iBeacons technology in a university campus. Evaluation of IncVoronoi with a side-by-side comparison with traditional fingerprinting techniques shows that it can achieve a consistent median accuracy of 2.8m under different scenarios with a low beacon density of one beacon every 44m2. Compared to fingerprinting techniques, whose accuracy degrades by at least 156%, this accuracy comes with no training overhead and is robust to the different user devices, different transmit powers, and over temporal changes in the environment. This highlights the promise of IncVoronoi as a next generation indoor localization system.
Detecting Ground Control Points via Convolutional Neural Network for Stereo Matching
Venue: arXiv cs.CV 2016
Year: 2016

In this paper, we present a novel approach to detect ground control points (GCPs) for stereo matching problem. First of all, we train a convolutional neural network (CNN) on a large stereo set, and compute the matching confidence of each pixel by using the trained CNN model. Secondly, we present a ground control points selection scheme according to the maximum matching confidence of each pixel. Finally, the selected GCPs are used to refine the matching costs, and we apply the new matching costs to perform optimization with semi-global matching algorithm for improving the final disparity maps. We evaluate our approach on the KITTI 2012 stereo benchmark dataset. Our experiments show that the proposed approach significantly improves the accuracy of disparity maps.
AndorEstimator: Android based Software Cost Estimation Application
Venue: arXiv cs.CY 2016
Year: 2016

The main aim of the proposed system is to assist the software development team to estimate the cost, effort and maintenance of the project under development. Android-based platform, namely MIT App Inventor is used for the development of application, which contains visual block programming language. The current study has following uniqueness of (1)Accuracy of results,(2)user friendly environment(3)no such application is available on android platform to the best of our knowledge. Questionnaire regarding CoCoMo model is developed and circulated by using objective qualitative method. Findings: The estimation module of our application is quite important with respect to facilitating the students of software engineering for performing CoCoMo-based cost estimation easily, and enabling the software developers for performing software cost estimation easily. The cost estimator based on CoCoMo model is developed on android platform however, to the best of our knowledge no such application is available. This system can be used by business and educational stakeholders, such as students, software developers, and business organizations
Noisy Broadcast Networks with Receiver Caching
Venue: arXiv cs.IT 2016
Year: 2016

We study noisy broadcast networks with local cache memories at the receivers, where the transmitter can pre-store information even before learning the receivers' requests. We mostly focus on packet-erasure broadcast networks with two disjoint sets of receivers: a set of weak receivers with all-equal erasure probabilities and equal cache sizes and a set of strong receivers with all-equal erasure probabilities and no cache memories. We present lower and upper bounds on the capacity-memory tradeoff of this network. The lower bound is achieved by a new joint cache-channel coding idea and significantly improves on schemes that are based on separate cache-channel coding. We discuss how this coding idea could be extended to more general discrete memoryless broadcast channels and to unequal cache sizes. Our upper bound holds for all stochastically degraded broadcast channels. For the described packet-erasure broadcast network, our lower and upper bounds are tight when there is a single weak receiver (and any number of strong receivers) and the cache memory size does not exceed a given threshold. When there are a single weak receiver, a single strong receiver, and two files, then we can strengthen our upper and lower bounds so as they coincide over a wide regime of cache sizes. Finally, we completely characterise the rate-memory tradeoff for general discrete-memoryless broadcast channels with arbitrary cache memory sizes and arbitrary (asymmetric) rates when all receivers always demand exactly the same file.
Asymmetric Move Selection Strategies in Monte-Carlo Tree Search: Minimizing the Simple Regret at Max Nodes
Venue: arXiv cs.AI 2016
Year: 2016

The combination of multi-armed bandit (MAB) algorithms with Monte-Carlo tree search (MCTS) has made a significant impact in various research fields. The UCT algorithm, which combines the UCB bandit algorithm with MCTS, is a good example of the success of this combination. The recent breakthrough made by AlphaGo, which incorporates convolutional neural networks with bandit algorithms in MCTS, also highlights the necessity of bandit algorithms in MCTS. However, despite the various investigations carried out on MCTS, nearly all of them still follow the paradigm of treating every node as an independent instance of the MAB problem, and applying the same bandit algorithm and heuristics on every node. As a result, this paradigm may leave some properties of the game tree unexploited. In this work, we propose that max nodes and min nodes have different concerns regarding their value estimation, and different bandit algorithms should be applied accordingly. We develop the Asymmetric-MCTS algorithm, which is an MCTS variant that applies a simple regret algorithm on max nodes, and the UCB algorithm on min nodes. We will demonstrate the performance of the Asymmetric-MCTS algorithm on the game of $9\times 9$ Go, $9\times 9$ NoGo, and Othello.
Note on families of pairing-friendly elliptic curves with small embedding degree
Venue: arXiv cs.CR 2016
Year: 2016

Pairing-based cryptographic schemes require so-called pairing-friendly elliptic curves, which have special properties. The set of pairing-friendly elliptic curves that are generated by given polynomials form a complete family. Although a complete family with a $ρ$-value of 1 is the ideal case, there is only one such example that is known, this was given by Barreto and Naehrig. We prove that there are no ideal families with embedding degree 3, 4, or 6 and that many complete families with embedding degree 8 or 12 are nonideal, even if we chose noncyclotomic families.
Proving Liveness of Parameterized Programs
Venue: arXiv cs.LO 2016
Year: 2016

Correctness of multi-threaded programs typically requires that they satisfy liveness properties. For example, a program may require that no thread is starved of a shared resource, or that all threads eventually agree on a single value. This paper presents a method for proving that such liveness properties hold. Two particular challenges addressed in this work are that (1) the correctness argument may rely on global behaviour of the system (e.g., the correctness argument may require that all threads collectively progress towards "the good thing" rather than one thread progressing while the others do not interfere), and (2) such programs are often designed to be executed by any number of threads, and the desired liveness properties must hold regardless of the number of threads that are active in the program.
Modeling of human society as a locally interacting product-potential networks of automaton
Venue: arXiv cs.SI 2016
Year: 2016

The central problems in social sciences concern the social and psychological mechanisms and conditions required for the emergence and stability of human groups. The present article is dedicated to the problem of stability of human groups. We model human groups using local interacting systems of automaton with relations and reactions and using the structural balance theory. The 'structural balance theory' ties the emergence of a human group with the human actor's thoughts about how another actor treats him and his perception of actors. The Cartwright and Harary formalization the concept of balance theory within a graph theoretical setting unable to get a number of mathematical results pertaining to an algebraic formulation of the theory of balance in signed networks/graphs. The deeper generalization of 'balance theory' as the smooth product-potential fields on domain gives us the ability to create theory of 'smooth product potential social fields'. We then find that all discrete product-potential system tightly connect with other process - process multiplication on the randomly chosen matrices and we find connections between stationary measures and some algebraic objects.
Audio Event Detection using Weakly Labeled Data
Venue: arXiv cs.SD 2016
Year: 2016

Acoustic event detection is essential for content analysis and description of multimedia recordings. The majority of current literature on the topic learns the detectors through fully-supervised techniques employing strongly labeled data. However, the labels available for majority of multimedia data are generally weak and do not provide sufficient detail for such methods to be employed. In this paper we propose a framework for learning acoustic event detectors using only weakly labeled data. We first show that audio event detection using weak labels can be formulated as an Multiple Instance Learning problem. We then suggest two frameworks for solving multiple-instance learning, one based on support vector machines, and the other on neural networks. The proposed methods can help in removing the time consuming and expensive process of manually annotating data to facilitate fully supervised learning. Moreover, it can not only detect events in a recording but can also provide temporal locations of events in the recording. This helps in obtaining a complete description of the recording and is notable since temporal information was never known in the first place in weakly labeled data.
Capacity and Degree-of-Freedom of OFDM Channels with Amplitude Constraint
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we study the capacity and degree-of-freedom (DoF) scaling for the continuous-time amplitude limited AWGN channels in radio frequency (RF) and intensity modulated optical communication (OC) channels. More precisely, we study how the capacity varies in terms of the OFDM block transmission time $T$, bandwidth $W$, amplitude $A$, and the noise spectral density $N_0$. We first find suitable discrete encoding spaces for both cases, and prove that they are convex sets that have a semi-definite programming (SDP) representation. Using tools from convex geometry, we find lower and upper bounds on the volume of these encoding sets, which we exploit to drive pretty sharp lower and upper bounds on the capacity. We also study a practical Tone-Reservation (TR) encoding algorithm and prove that its performance can be characterized by the statistical width of an appropriate convex set. Recently, it has been observed that in high-dimensional estimation problems under constraints such as those arisen in Compressed Sensing (CS) statistical width plays a crucial role. We discuss some of the implications of the resulting statistical width on the performance of the TR. We also provide numerical simulations to validate these observations.
Convolutive superposition for multicarrier cognitive radio systems
Venue: arXiv cs.IT 2016
Year: 2016

Recently, we proposed a spectrum-sharing paradigm for single-carrier cognitive radio (CR) networks, where a secondary user (SU) is able to maintain or even improve the performance of a primary user (PU) transmission, while also obtaining a low-data rate channel for its own communication. According to such a scheme, a simple multiplication is used to superimpose one SU symbol on a block of multiple PU symbols.The scope of this paper is to extend such a paradigm to a multicarrier CR network, where the PU employs an orthogonal frequency-division multiplexing (OFDM) modulation scheme. To improve its achievable data rate, besides transmitting over the subcarriers unused by the PU, the SU is also allowed to transmit multiple block-precoded symbols in parallel over the OFDM subcarriers used by the primary system. Specifically, the SU convolves its block-precoded symbols with the received PU data in the time-domain, which gives rise to the term convolutive superposition. An information-theoretic analysis of the proposed scheme is developed, which considers different amounts of network state information at the secondary transmitter, as well as different precoding strategies for the SU. Extensive simulations illustrate the merits of our analysis and designs, in comparison with conventional CR schemes, by considering as performance indicators the ergodic capacity of the considered systems.
Topological language for RNA
Venue: arXiv cs.FL 2016
Year: 2016

In this paper we introduce a novel, context-free grammar, {\it RNAFeatures$^*$}, capable of generating any RNA structure including pseudoknot structures (pk-structure). We represent pk-structures as orientable fatgraphs, which naturally leads to a filtration by their topological genus. Within this framework, RNA secondary structures correspond to pk-structures of genus zero. {\it RNAFeatures$^*$} acts on formal, arc-labeled RNA secondary structures, called $λ$-structures. $λ$-structures correspond one-to-one to pk-structures together with some additional information. This information consists of the specific rearrangement of the backbone, by which a pk-structure can be made cross-free. {\it RNAFeatures$^*$} is an extension of the grammar for secondary structures and employs an enhancement by labelings of the symbols as well as the production rules. We discuss how to use {\it RNAFeatures$^*$} to obtain a stochastic context-free grammar for pk-structures, using data of RNA sequences and structures. The induced grammar facilitates fast Boltzmann sampling and statistical analysis. As a first application, we present an $O(n log(n))$ runtime algorithm which samples pk-structures based on ninety tRNA sequences and structures from the Nucleic Acid Database (NDB).
Tracking Illicit Drug Dealing and Abuse on Instagram using Multimodal Analysis
Venue: arXiv cs.SI 2016
Year: 2016

Illicit drug trade via social media sites, especially photo-oriented Instagram, has become a severe problem in recent years. As a result, tracking drug dealing and abuse on Instagram is of interest to law enforcement agencies and public health agencies. In this paper, we propose a novel approach to detecting drug abuse and dealing automatically by utilizing multimodal data on social media. This approach also enables us to identify drug-related posts and analyze the behavior patterns of drug-related user accounts. To better utilize multimodal data on social media, multimodal analysis methods including multitask learning and decision-level fusion are employed in our framework. Experiment results on expertly labeled data have demonstrated the effectiveness of our approach, as well as its scalability and reproducibility over labor-intensive conventional approaches.
Calculational Design of Information Flow Monitors (extended version)
Venue: arXiv cs.CR 2016
Year: 2016

Fine grained information flow monitoring can in principle address a wide range of security and privacy goals, for example in web applications. But it is very difficult to achieve sound monitoring with acceptable runtime cost and sufficient precision to avoid impractical restrictions on programs and policies. We present a systematic technique for design of monitors that are correct by construction. It encompasses policies with downgrading. The technique is based on abstract interpretation which is a standard basis for static analysis of programs. This should enable integration of a wide range of analysis techniques, enabling more sophisticated engineering of monitors to address the challenges of precision and scaling to widely used programming languages.
Asymptotic Analysis of Multicell Massive MIMO over Rician Fading Channels
Venue: arXiv cs.IT 2016
Year: 2016

This work considers the downlink of a multicell massive MIMO system in which $L$ base stations (BSs) of $N$ antennas each communicate with $K$ single-antenna user equipments randomly positioned in the coverage area. Within this setting, we are interested in evaluating the sum rate of the system when MRT and RZF are employed under the assumption that each intracell link forms a MIMO Rician fading channel. The analysis is conducted assuming that $N$ and $K$ grow large with a non-trivial ratio $N/K$ under the assumption that the data transmission in each cell is affected by channel estimation errors, pilot contamination, and an arbitrary large scale attenuation. Numerical results are used to validate the asymptotic analysis in the finite system regime and to evaluate the network performance under different settings. The asymptotic results are also instrumental to get insights into the interplay among system parameters.
Hierarchical Partition-Based Anonymous Routing Protocol(HPAR) in Manet for Efficient and Secure Transmission
Venue: arXiv cs.NI 2016
Year: 2016

Anonymous routing protocols are used in MANET's to hide the nodes from outsiders in order to protect from various attacks. HPAR partitions the network area dynamically into zones and chooses nodes in zones randomly as intermediate relay nodes .This relay nodes help in secure routing. In HPAR anonymity protection is given to source, destination and route. HPAR have low cost and provide high level of protection. It has techniques to counter various attacks.
An Algorithm for Komlós Conjecture Matching Banaszczyk's bound
Venue: arXiv cs.DS 2016
Year: 2016

We consider the problem of finding a low discrepancy coloring for sparse set systems where each element lies in at most t sets. We give an efficient algorithm that finds a coloring with discrepancy O((t log n)^{1/2}), matching the best known non-constructive bound for the problem due to Banaszczyk. The previous algorithms only achieved an O(t^{1/2} log n) bound. The result also extends to the more general Komlós setting and gives an algorithmic O(log^{1/2} n) bound.