OpenRaiser/Intern-Atlas huggingface dataset:
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text
Venue: arXiv cs.CL 2015
Year: 2015

We advance the state of the art in biomolecular interaction extraction with three contributions: (i) We show that deep, Abstract Meaning Representations (AMR) significantly improve the accuracy of a biomolecular interaction extraction system when compared to a baseline that relies solely on surface- and syntax-based features; (ii) In contrast with previous approaches that infer relations on a sentence-by-sentence basis, we expand our framework to enable consistent predictions over sets of sentences (documents); (iii) We further modify and expand a graph kernel learning framework to enable concurrent exploitation of automatically induced AMR (semantic) and dependency structure (syntactic) representations. Our experiments show that our approach yields interaction extraction systems that are more robust in environments where there is a significant mismatch between training and test conditions.
Polynomial bounds for decoupling, with applications
Venue: arXiv cs.DM 2015
Year: 2015

Let f(x) = f(x_1, ..., x_n) = \sum_{|S| <= k} a_S \prod_{i \in S} x_i be an n-variate real multilinear polynomial of degree at most k, where S \subseteq [n] = {1, 2, ..., n}. For its "one-block decoupled" version, f~(y,z) = \sum_{|S| <= k} a_S \sum_{i \in S} y_i \prod_{j \in Sı} z_j, we show tail-bound comparisons of the form Pr[|f~(y,z)| > C_k t] <= D_k Pr[f(x) > t]. Our constants C_k, D_k are significantly better than those known for "full decoupling". For example, when x, y, z are independent Gaussians we obtain C_k = D_k = O(k); when x, y, z, Rademacher random variables we obtain C_k = O(k^2), D_k = k^{O(k)}. By contrast, for full decoupling only C_k = D_k = k^{O(k)} is known in these settings. We describe consequences of these results for query complexity (related to conjectures of Aaronson and Ambainis) and for analysis of Boolean functions (including an optimal sharpening of the DFKO Inequality).
PJAIT Systems for the IWSLT 2015 Evaluation Campaign Enhanced by Comparable Corpora
Venue: arXiv cs.CL 2015
Year: 2015

In this paper, we attempt to improve Statistical Machine Translation (SMT) systems on a very diverse set of language pairs (in both directions): Czech - English, Vietnamese - English, French - English and German - English. To accomplish this, we performed translation model training, created adaptations of training settings for each language pair, and obtained comparable corpora for our SMT systems. Innovative tools and data adaptation techniques were employed. The TED parallel text corpora for the IWSLT 2015 evaluation campaign were used to train language models, and to develop, tune, and test the system. In addition, we prepared Wikipedia-based comparable corpora for use with our SMT system. This data was specified as permissible for the IWSLT 2015 evaluation. We explored the use of domain adaptation techniques, symmetrized word alignment models, the unsupervised transliteration models and the KenLM language modeling tool. To evaluate the effects of different preparations on translation results, we conducted experiments and used the BLEU, NIST and TER metrics. Our results indicate that our approach produced a positive impact on SMT quality.
Using Functional Programming for Development of Distributed, Cloud and Web Applications in F#
Venue: arXiv cs.PL 2015
Year: 2015

In this paper, we argue that modern functional programming languages - in particular, FSharp on the .NET platform - are well suited for the development of distributed, web and cloud applications on the Internet. We emphasize that FSharp can be successfully used in a range of scenarios - starting from simple ASP.NET web applications, and including cloud data processing tasks and data-driven web applications. In particular, we show how some of the FSharp features (eg. quotations) can be effectively used to develop a distributed web system using single code-base, and describe the commercial WebSharper project by Intellifactory for building distributed client-server web applications, as well as research library that uses Windows Azure for parametric sweep computational tasks.
Algorithmic decidability of Engel's property for automaton groups
Venue: arXiv cs.FL 2015
Year: 2015

We consider decidability problems associated with Engel's identity ($[\cdots[[x,y],y],\dots,y]=1$ for a long enough commutator sequence) in groups generated by an automaton. We give a partial algorithm that decides, given $x,y$, whether an Engel identity is satisfied. It succeeds, importantly, in proving that Grigorchuk's $2$-group is not Engel. We consider next the problem of recognizing Engel elements, namely elements $y$ such that the map $x\mapsto[x,y]$ attracts to $\{1\}$. Although this problem seems intractable in general, we prove that it is decidable for Grigorchuk's group: Engel elements are precisely those of order at most $2$. Our computations were implemented using the package FR within the computer algebra system GAP.
Combinatorial Message Sharing and a New Achievable Region for Multiple Descriptions
Venue: arXiv cs.IT 2015
Year: 2015

This paper presents a new achievable rate-distortion region for the general L channel multiple descriptions problem. A well known general region for this problem is due to Venkataramani, Kramer and Goyal (VKG) [1]. Their encoding scheme is an extension of the El-Gamal-Cover (EC) and Zhang- Berger (ZB) coding schemes to the L channel case and includes a combinatorial number of refinement codebooks, one for each subset of the descriptions. As in ZB, the scheme also allows for a single common codeword to be shared by all descriptions. This paper proposes a novel encoding technique involving Combinatorial Message Sharing (CMS), where every subset of the descriptions may share a distinct common message. This introduces a combinatorial number of shared codebooks along with the refinement codebooks of [1]. We derive an achievable rate-distortion region for the proposed technique, and show that it subsumes the VKG region for general sources and distortion measures. We further show that CMS provides a strict improvement of the achievable region for any source and distortion measures for which some 2-description subset is such that ZB achieves points outside the EC region. We then show a more surprising result: CMS outperforms VKG for a general class of sources and distortion measures, including scenarios where the ZB and EC regions coincide for all 2-description subsets. In particular, we show that CMS strictly improves on VKG, for the L-channel quadratic Gaussian MD problem, for all L greater than or equal to 3, despite the fact that the EC region is complete for the corresponding 2-descriptions problem. Using the encoding principles derived, we show that the CMS scheme achieves the complete rate-distortion region for several asymmetric cross-sections of the L-channel quadratic Gaussian MD problem.
Interference Alignment for the K-user Interference Channel with Imperfect CSI
Venue: arXiv cs.IT 2015
Year: 2015

In this paper we explore the information-theoretic aspects of interference alignment and its relation to channel state information (CSI). For the $K-$user interference channel using different changing patterns between different users, we propose several methods to align some parts of interferences and to increase what is achieved by time sharing method. For more practical case when all the channel links connected to the same destination have the same changing pattern, we find an upper-bound and analyze it for the large interference channel network. This result shows that when the size of the network increases, the upper-bound value goes to $\frac{\sqrt{K}}{2}$. For the fast fading channel when all the channels have the same changing pattern, we show that when the direct links have different characteristic functions (channel permutation or memory), in the absence of half part of CSI (cross links) at both transmitters and receivers, one can achieve $K/2$ degrees-of-freedom (DoF). Also by the converse proof we show that this is the minimum channel information to achieve maximum DoF of $\frac{K}{2}$. Throughout this work, this fact has been pinpointed to prove statements about more general partial state CSI and achievable DoF. In other words, for the 3-user fully connected interference channel we find out while $\frac{3}{2}$ lies in achievable DoF, we don't need to know half part of the CSI. Also, the result has been extended to a more general form for $K-$user interference channel and through the converse proof, its functionality on channel state is proved to be optimum.
The generalized likelihood decoder: random coding and expurgated bounds
Venue: arXiv cs.IT 2015
Year: 2015

The likelihood decoder is a stochastic decoder that selects the decoded message at random, using the posterior distribution of the true underlying message given the channel output. In this work, we study a generalized version of this decoder where the posterior is proportional to a general function that depends only on the joint empirical distribution of the output vector and the codeword. This framework allows both mismatched versions and universal (MMI) versions of the likelihood decoder, as well as the corresponding ordinary deterministic decoders, among many others. We provide a direct analysis method that yields the exact random coding exponent (as opposed to separate upper bounds and lower bounds that turn out to be compatible, which were derived earlier by Scarlett et al. We also extend the result from pure channel coding to combined source and channel coding (random binning followed by random channel coding) with side information available to the decoder. Finally, returning to pure channel coding, we derive also an expurgated exponent for the stochastic likelihood decoder, which turns out to be at least as tight (and in some cases, strictly so) as the classical expurgated exponent of the maximum likelihood decoder, even though the stochastic likelihood decoder is suboptimal.
Improving Type Error Messages in OCaml
Venue: arXiv cs.PL 2015
Year: 2015

Cryptic type error messages are a major obstacle to learning OCaml or other ML-based languages. In many cases, error messages cannot be interpreted without a sufficiently-precise model of the type inference algorithm. The problem of improving type error messages in ML has received quite a bit of attention over the past two decades, and many different strategies have been considered. The challenge is not only to produce error messages that are both sufficiently concise and systematically useful to the programmer, but also to handle a full-blown programming language and to cope with large-sized programs efficiently. In this work, we present a modification to the traditional ML type inference algorithm implemented in OCaml that, by significantly reducing the left-to-right bias, allows us to report error messages that are more helpful to the programmer. Our algorithm remains fully predictable and continues to produce fairly concise error messages that always help making some progress towards fixing the code. We implemented our approach as a patch to the OCaml compiler in just a few hundred lines of code. We believe that this patch should benefit not just to beginners, but also to experienced programs developing large-scale OCaml programs.
A Simple and Practical Linear Algebra Library Interface with Static Size Checking
Venue: arXiv cs.PL 2015
Year: 2015

Linear algebra is a major field of numerical computation and is widely applied. Most linear algebra libraries (in most programming languages) do not statically guarantee consistency of the dimensions of vectors and matrices, causing runtime errors. While advanced type systems--specifically, dependent types on natural numbers--can ensure consistency among the sizes of collections such as lists and arrays, such type systems generally require non-trivial changes to existing languages and application programs, or tricky type-level programming. We have developed a linear algebra library interface that verifies the consistency (with respect to dimensions) of matrix operations by means of generative phantom types, implemented via fairly standard ML types and module system. To evaluate its usability, we ported to it a practical machine learning library from a traditional linear algebra library. We found that most of the changes required for the porting could be made mechanically, and changes that needed human thought are minor.
Stable Distributions as Noise Models for Molecular Communication
Venue: arXiv cs.IT 2015
Year: 2015

In this work, we consider diffusion-based molecular communication timing channels. Three different timing channels are presented based on three different modulation techniques, i.e., i) modulation of the release timing of the information particles, ii) modulation on the time between two consecutive information particles of the same type, and iii) modulation on the time between two consecutive information particles of different types. We show that each channel can be represented as an additive noise channel, where the noise follows one of the subclasses of stable distributions. We provide expressions for the probability density function of the noise terms, and numerical evaluations for the probability density function and cumulative density function. We also show that the tails are longer than Gaussian distribution, as expected.
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation
Venue: arXiv cs.LG 2015
Year: 2015

We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features. Under the generic RegBayes (regularized Bayesian inference) framework, we handily incorporate the prediction loss with probabilistic inference of a Bayesian model; set distinct regularization parameters for different types of links to handle the imbalance issue in real networks; and unify the analysis of both the smooth logistic log-loss and the piecewise linear hinge loss. For the nonconjugate posterior inference, we present a simple Gibbs sampler via data augmentation, without making restricting assumptions as done in variational methods. We further develop an approximate sampler using stochastic gradient Langevin dynamics to handle large networks with hundreds of thousands of entities and millions of links, orders of magnitude larger than what existing LFRM models can process. Extensive studies on various real networks show promising performance.
On The Continuous Steering of the Scale of Tight Wavelet Frames
Venue: arXiv cs.CV 2015
Year: 2015

In analogy with steerable wavelets, we present a general construction of adaptable tight wavelet frames, with an emphasis on scaling operations. In particular, the derived wavelets can be "dilated" by a procedure comparable to the operation of steering steerable wavelets. The fundamental aspects of the construction are the same: an admissible collection of Fourier multipliers is used to extend a tight wavelet frame, and the "scale" of the wavelets is adapted by scaling the multipliers. As an application, the proposed wavelets can be used to improve the frequency localization. Importantly, the localized frequency bands specified by this construction can be scaled efficiently using matrix multiplication.
Digital Genesis: Computers, Evolution and Artificial Life
Venue: arXiv cs.NE 2015
Year: 2015

The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting with the early theoretical work of John von Neumann and the pioneering experimental work of Nils Aall Barricelli. We argue that evolutionary thinking and artificial life will continue to play an integral role in the future development of the digital world.
Wavelet Based Load Models from AMI Data
Venue: arXiv cs.CE 2015
Year: 2015

A major challenge of using AMI data in power system analysis is the large size of the data sets. For rapid analysis that addresses historical behavior of systems consisting of a few hundred feeders, all of the AMI load data can be loaded into memory and used in a power flow analysis. However, if a system contains thousands of feeders then the handling of the AMI data in the analysis becomes more challenging. The work here seeks to demonstrate that the information contained in large AMI data sets can be compressed into accurate load models using wavelets. Two types of wavelet based load models are considered, the multi-resolution wavelet load model for each individual customer and the classified wavelet load model for customers that share similar load patterns. The multi-resolution wavelet load model compresses the data, and the classified wavelet load model further compresses the data. The method of grouping customers into classes using the wavelet based classification technique is illustrated.
Learning to Point and Count
Venue: arXiv cs.CV 2015
Year: 2015

This paper proposes the problem of point-and-count as a test case to break the what-and-where deadlock. Different from the traditional detection problem, the goal is to discover key salient points as a way to localize and count the number of objects simultaneously. We propose two alternatives, one that counts first and then point, and another that works the other way around. Fundamentally, they pivot around whether we solve "what" or "where" first. We evaluate their performance on dataset that contains multiple instances of the same class, demonstrating the potentials and their synergies. The experiences derive a few important insights that explains why this is a much harder problem than classification, including strong data bias and the inability to deal with object scales robustly in state-of-art convolutional neural networks.
Computational Models for Multiview Dense Depth Maps of Dynamic Scene
Venue: arXiv cs.CV 2015
Year: 2015

This paper reviews the recent progresses of the depth map generation for dynamic scene and its corresponding computational models. This paper mainly covers the homogeneous ambiguity models in depth sensing, resolution models in depth processing, and consistency models in depth optimization. We also summarize the future work in the depth map generation.
Medical Wearable Technologies: Applications, Problems and Solutions
Venue: arXiv cs.CY 2015
Year: 2015

The focus of this paper is on wearable technologies which are increasingly being employed in the medical field. From smart watches to smart glasses, from electronic textile to data gloves; several gadgets are playing important roles in diagnosis and treatment of various medical conditions. The threats posed by these technologies are another matter of concern that must be seriously taken into account. Numerous threats ranging from data privacy to big data problems are facing us as adverse effects of these technologies. The paper analyses the application areas and challenges of wearable technologies from a technical and ethical point of view and presents solutions to possible threats.
On hybrid circuits exploiting thermistive properties of slime mould
Venue: arXiv cs.ET 2015
Year: 2015

Slime mould Physarum polycephalum is a single cell visible by unaided eye. Let the slime mould span two electrodes with a single protoplasmic tube: if the tube is heated to approximately 40°C, the electrical resistance of the protoplasmic tube increases from 3 MΩ to approximatively 10'000 MΩ. The organism's resistance is not proportional nor correlated to the temperature of its environment. Slime mould can therefore not be considered as a thermistor but rather as a thermic switch. We employ the P. polycephalum thermic switch to prototype hybrid electrical analog summator, NAND gates, and cascade the gates into Flip-Flop latch. Computing operations performed on this bio-hybrid computing circuitry feature high repeatability, reproducibility and comparably low propagation delays
Robust Mediators in Large Games
Venue: arXiv cs.GT 2015
Year: 2015

A mediator is a mechanism that can only suggest actions to players, as a function of all agents' reported types, in a given game of incomplete information. We study what is achievable by two kinds of mediators, "strong" and "weak." Players can choose to opt-out of using a strong mediator but cannot misrepresent their type if they opt-in. Such a mediator is "strong" because we can view it as having the ability to verify player types. Weak mediators lack this ability--- players are free to misrepresent their type to a weak mediator. We show a striking result---in a prior-free setting, assuming only that the game is large and players have private types, strong mediators can implement approximate equilibria of the complete-information game. If the game is a congestion game, then the same result holds using only weak mediators. Our result follows from a novel application of differential privacy, in particular, a variant we propose called joint differential privacy.
Multi-path Model and Sensitivity Analysis for Galvanic Coupled Intra-body Communication through Layered Tissue
Venue: arXiv cs.NI 2015
Year: 2015

New medical procedures promise continuous patient monitoring and drug delivery through implanted sensors and actuators. When over the air wireless radio frequency (OTA-RF) links are used for intra-body implant communication, the network incurs heavy energy costs owing to absorption within the human tissue. With this motivation, we explore an alternate form of intra-body communication that relies on weak electrical signals, instead of OTA-RF. To demonstrate the feasibility of this new paradigm for enabling communication between sensors and actuators embedded within the tissue, or placed on the surface of the skin, we develop a rigorous analytical model based on galvanic coupling of low energy signals. The main contributions in this paper are: (i) developing a suite of analytical expressions for modeling the resulting communication channel for weak electrical signals in a three dimensional multi-layered tissue structure, (ii) validating and verifying the model through extensive finite element simulations, published measurements in existing literature, and experiments conducted with porcine tissue, (iii) designing the communication framework with safety considerations, and analyzing the influence of different network and hardware parameters such as transmission frequency and electrode placements. Our results reveal a close agreement between theory, simulation, literature and experimental findings, pointing to the suitability of the model for quick and accurate channel characterization and parameter estimation for networked and implanted sensors.
Deciding Orthogonality in Construction-A Lattices
Venue: arXiv cs.DM 2015
Year: 2015

Lattices are discrete mathematical objects with widespread applications to integer programs as well as modern cryptography. A fundamental problem in both domains is the Closest Vector Problem (popularly known as CVP). It is well-known that CVP can be easily solved in lattices that have an orthogonal basis \emph{if} the orthogonal basis is specified. This motivates the orthogonality decision problem: verify whether a given lattice has an orthogonal basis. Surprisingly, the orthogonality decision problem is not known to be either NP-complete or in P. In this paper, we focus on the orthogonality decision problem for a well-known family of lattices, namely Construction-A lattices. These are lattices of the form $C+q\mathbb{Z}^n$, where $C$ is an error-correcting $q$-ary code, and are studied in communication settings. We provide a complete characterization of lattices obtained from binary and ternary codes using Construction-A that have an orthogonal basis. We use this characterization to give an efficient algorithm to solve the orthogonality decision problem. Our algorithm also finds an orthogonal basis if one exists for this family of lattices. We believe that these results could provide a better understanding of the complexity of the orthogonality decision problem for general lattices.