Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Coding of Visual Scenes by Grouping and Segmentation

The goal of this chapter is to present computational theories of scene coding by image segmentation and to suggest their relevance for understanding visual cortical function and mechanisms. We will first introduce computational theories of image and scene segmentation and show their relationship to efficient encoding. Then we discuss and evaluate the relevant physiological data in the context of these computational frameworks. It is hoped that this will stimulate quantitative neurophysiological investigations of scene segmentation guided by computational theories. Our central conjecture is that areas V1 and V2, in addition to encoding fine details of images in terms of filter responses, compute a segmentation of images which allows a more compact and parsimonious encoding of images in terms of the properties of regions and surfaces in the visual scene. This conjecture is based on the observation that neurons and their retinotopic arrangement in these visual areas can represent information precisely, thus furnishing an appropriate computational and representational infrastructure for this task. Segmentation detects and extracts coherent regions in an image and then encodes the image in terms of probabilistic models of surfaces and regions in it, in the spirit of Shannon's theory of information. This representation facilitates visual reasoning at the level of regions and their boundaries, without worrying too much about all the small details in the image. Figure 8.1 gives three examples which illustrate the meaning of higher-level efficient encoding of scenes. Firstly, consider Kanizsa's famous illusory triangle (figure 8.1a) [28]. It is simpler to explain it as a white triangle in front of, and partially occluding, three black circular disks rather than as three Pac-Men who are accidentally aligned to each other. Indeed, this simple explanation is what humans perceive and, in fact, the perception of a triangle is so strong that we hallucinate the surface of the triangle as being brighter than the background and perceive sharp boundaries to the triangle even at places where there are no direct visual cues. Secondly, when confronted with the image shown in figure 8.1b [58], we perceive it as a group of convex spheres mixed together with 142 8 Efficient Coding of Visual Scenes by Grouping and Segmentation Tai Sing Lee and Alan L. Yuille a group of concave indentations (e.g. an egg carton partly filled with eggs). This interpretation is more parsimonious than describing every detail of the intensity shading and other image features. Thirdly, at first glance, …
Efficient Coding of Visual Scenes by Grouping and Segmentation : Theoretical Principles and Biological Evidence

Introduction The goal of this chapter is to present computational theories of scene coding by image segmentation and to suggest their relevance for understanding visual cortical function and mechanisms. We will first introduce computational theories of image and scene segmentation and show their relationship to efficient encoding. Then we discuss and evaluate the relevant physiological data in the context of these computational frameworks. It is hoped that this will stimulate quantitative neurophysiological investigations of scene segmentation guided by computational theories. Our central conjecture is that areas V1 and V2, in addition to encoding fine details of images in terms of filter responses, compute a segmentation of images which allow a more compact and parsimonious encoding of images in terms of the properties of regions and surfaces in the visual scene. This conjecture is based on the observation that neurons and their retinotopic arrangement in these visual areas can represent information precisely, thus furnishing an appropriate computational and representational infrastructure for this task. Segmentation detects and extracts coherent regions in an image and then encode the image in terms of probabilistic models of surfaces and regions in it, in the spirit of Shannon's theory of information. This representation facilitates visual reasoning at the level of regions and their boundaries, without worrying too much about all the small details in the image. Figure 1 gives three examples which illustrate the meaning of higher level efficient encoding of scenes. Firstly, consider Kanizsa's (1979) famous illusory triangle (Figure 1a). It is simpler to explain it as a white triangle in front of, and partially occluding, three black circular discs rather than as three pac-mens which are accidentally aligned to each other. Indeed this simple explanation is what human perceive and, in fact, the perception of a triangle is so strong that we hallucinate the surface of the triangle as being brighter than the background and perceive sharp boundaries to the triangle even at places where there is no direct visual cues. Secondly, when confronted with the image shown in Figure 1b (Ramachandran 1988), we perceive it as a group of convex spheres mixed together with a group of concave indentations (e.g. an egg carton partly filled with eggs). This interpretation is more parsimonious than describing every detail of the intensity shading and other image features. Thirdly, at first glance, the image in Figure 1c (Gregory 1970) appears to be a collection of random dots …
3D Harmonic Loss: Towards Task-consistent and Time-friendly 3D Object Detection on Edge for Intelligent Transportation System

—Edge computing-based 3D perception has received attention in intelligent transportation systems (ITS) because real-time monitoring of trafﬁc candidates potentially strengthens Vehicle-to-Everything (V2X) orchestration. Thanks to the capability of precisely measuring the depth information on surroundings from LiDAR, the increasing studies focus on lidar-based 3D detection, which signiﬁcantly promotes the development of 3D perception. Few methods met the real-time requirement of edge deployment because of high computation-intensive operations. Moreover, an inconsistency problem of object detection remains uncovered in the pointcloud domain due to large sparsity. This paper thoroughly analyses this problem, comprehensively roused by recent works on determining inconsistency problems in the image specialisation. Therefore, we proposed a 3D harmonic loss function to relieve the pointcloud based inconsistent predictions. Moreover, the feasibility of 3D harmonic loss is demonstrated from a mathematical optimization perspective. The KITTI dataset and DAIR-V2X-I dataset are used for simulations, and our proposed method considerably improves the performance than benchmark models. Further, the simulative deployment on an edge device (Jetson Xavier TX) validates our proposed model’s efﬁciency. Our code is open-source and publicly available: https://github.com/XJTU-Haolin/TT3D.
The encyclopedia of integer sequences

Description of the Book: Description of a Typical Entry. Arrangement of a Table. Number of Terms Given. References. What Sequences are Included? The Figures. How to Handle a Strange Sequence: How to See if a Sequence Is in the Table. If the Sequence is Not in the Table. Finding the Next Term. Recurrences and Generating Functions. Analysis of Differences. Other Methods for Hand Analysis. Transformations of Sequences. Methods for Computer Investigation of Sequences. The On-line Versions of the Encyclopedia. The Floppy Disk. Further Topics: Applications. History. Differences from the 1973 Book. Future Plans. Acknowledgments. The Table of Sequences. Bibliography. Index.
Quantum non-malleability and authentication ( extended abstract )

In its most basic form, encryption ensures the secrecy of transmissions against eavesdroppers. Besides secrecy, another desirable property is non-malleability, which guarantees that an active adversary cannot modify the plaintext by manipulating the ciphertext. In the classical setting, secrecy and non-malleability are independent: there are schemes which satisfy secrecy but are malleable, and schemes which are non-malleable but transmit the plaintext in the clear. If both secrecy and nonmalleability are desired, then pairwise-independent permutations provide information-theoretically perfect (one-time) security [12]. In the setting of quantum information, encryption is the task of transmitting quantum states over a completely insecure quantum channel. Information-theoretic secrecy for quantum encryption is well-understood. Moreover, significant progress has been made on more advanced constructions, such as authenticated encryption [5], secure two-party computation [10], blind computation [8], quantum fully-homomorphic encryption [9], and many more. Despite this high-level progress, a basic aspect of quantum encryption remains largely unstudied. Indeed, quantum non-malleability was considered in only one previous work, by Ambainis, Bouda and Winter [4]. Their definition (which we call ABW-NM) requires secrecy, and that the “effective channel” Dec ◦ Λ ◦ Enc of any adversary Λ is trivial1. Unlike non-malleability, the closely-related subject of quantum authentication (where decryption is allowed to reject) has received significant attention (see, e.g., [1, 5, 7, 10, 11].) In this setting, there are two definitions. The widely-adopted definition of Dupuis, Nielsen and Salvail (DNS-authentication) asks that, regardless of whether decryption rejects, the average effective channel of any adversary does not touch the plaintext [10]. A more recent definition of Garg, Yuen and Zhandry (GYZ-authentication) asks that, in the accept case, the adversary does not touch the plaintext with high probability over the key (rather than on average) [11].
Approximate Policy Iteration with a Policy Language Bias: Solving Relational Markov Decision Processes

We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual value-function learning step with a learning step in policy space. This is advantageous in domains where good policies are easier to represent and learn than the corresponding value functions, which is often the case for the relational MDPs we are interested in. In order to apply API to such problems, we introduce a relational policy language and corresponding learner. In addition, we introduce a new bootstrapping routine for goal-based planning domains, based on random walks. Such bootstrapping is necessary for many large relational MDPs, where reward is extremely sparse, as API is ineffective in such domains when initialized with an uninformed policy. Our experiments show that the resulting system is able to find good policies for a number of classical planning domains and their stochastic variants by solving them as extremely large relational MDPs. The experiments also point to some limitations of our approach, suggesting future work.
Daytime midlatitude plasma depletions observed by Swarm: Topside signatures of the rocket exhaust

The daytime midlatitude plasma depletions (DMLPDs) observed on 22 May 2014 and 20 May 2015 by the Swarm constellation are not explained by any known natural phenomena. The DMLPDs were detected after rocket launches, and the DMLPD traces converged to the launch station. The event in 2015, for which sufficient total electron content (TEC) data are available, is accompanied with TEC depletion lasting for about 6 h. The persistence generally agrees with the lifetime expected for rocket exhaust depletions (REDs) which is determined by the recombination of the ionospheric oxygen ion with water molecules in the rocket exhaust. These results lead to the conclusion that DMLPDs are REDs in the topside. The RED characteristics identified from the observations on both days are (1) enhancement in electron temperature, (2) reduction in electron pressure, and (3) absence of substructures down to scale sizes of about 8 km (Nyquist's scale size).
Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints

Block diagonalization (BD) is a practically favorable precoding technique that eliminates the interuser interference in downlink multiuser multiple-input multiple-output (MIMO) systems. In this paper, we apply BD to the downlink transmission in a cooperative multi-cell system, where the signals from different base stations (BSs) to all the mobile stations (MSs) are jointly designed with the perfect knowledge of the downlink channels and transmit messages. Specifically, this paper studies the BD precoder design to maximize the weighted sum-rate achievable for all the MSs. The associated optimization problem can be formulated in an auxiliary MIMO broadcast channel (BC) with a set of transmit power constraints equivalent to those for different BSs in the multi-cell system. Based on convex optimization techniques, this paper designs an efficient algorithm to solve this problem, and derives the structure of the corresponding optimal BD precoding matrix. Moreover, for the special case of single-antenna BSs and MSs, it is shown that the proposed solution leads to the optimal zero-forcing beamforming (ZF-BF) precoder design for the multiple-input single-output (MISO) BC with the per-antenna power constraints.
Large $n$  Analysis of Amplify-and-Forward MIMO Relay Channels With Correlated Rayleigh Fading

In this correspondence, the cumulants of the mutual information of the flat Rayleigh fading two-hop amplify-and-forward multiple-input multiple-output (MIMO) relay channel under independent and identically distributed (i.i.d.) Gaussian input vectors are derived in the large array limit. The analysis is based on the replica trick and covers both spatially independent and Kronecker correlated fading. Beamforming at all terminals is restricted to weight matrices that are independent of the channel realization and constant over time. Expressions for mean and variance of the mutual information are obtained. Their parameters are determined by a nonlinear equation system. All higher cumulants are shown to vanish as the number of antennas per terminal, n, grows to infinity. In conclusion, the distribution of the mutual information I becomes Gaussian in the large n limit. In this asymptotic regime, it is completely characterized by the expressions obtained for mean and variance of I, which are in Theta(n) and O(1), respectively. Comparisons with simulation results show that the asymptotic results serve as excellent approximations for systems with only few antennas at each terminal.
Fast mixing of parallel Glauber dynamics and low-delay CSMA scheduling

Glauber dynamics is a powerful tool to generate randomized, approximate solutions to combinatorially difficult problems. It has been recently used to design distributed CSMA scheduling algorithms for multi-hop wireless networks. In this paper, we derive bounds on the mixing time of a generalization of Glauber dynamics where multiple links update their states in parallel and the fugacity of each link can be different. The results are used to prove that the average queue length (and hence, the delay) under the parallel-Glauber-dynamics-based CSMA grows polynomially in the number of links for wireless networks with bounded-degree interference graphs when the arrival rate lies in a fraction of the capacity region. Other versions of adaptive CSMA can be analyzed similarly.
Energy-Efficient Scheduling for mmWave Backhauling of Small Cells in Heterogeneous Cellular Networks

Heterogeneous cellular networks (HCNs) are emerging as a promising candidate for the fifth-generation (5G) mobile network. With base stations (BSs) of small cells densely deployed, the cost-effective, flexible, and green backhaul solution has become one of the most urgent and critical challenges. With vast amounts of spectrum available, wireless backhaul in the millimeter-wave (mmWave) band is able to provide transmission rates of several gigabits per second. The mmWave backhaul utilizes beamforming to achieve directional transmission, and concurrent transmissions under low interlink interference can be enabled to improve network capacity. To achieve an energy-efficient solution for mmWave backhauling, we first formulate the problem of minimizing the energy consumption via concurrent transmission scheduling and power control into a mixed integer nonlinear program (MINLP). Then, we develop an energy-efficient and practical mmWave backhauling scheme, which consists of the maximum independent set (MIS)-based scheduling algorithm and the power control algorithm. We also theoretically analyze the conditions that our scheme reduces energy consumption, as well as the choice of the interference threshold. Through extensive simulations under various traffic patterns and system parameters, we demonstrate the superior performance of our scheme in terms of energy efficiency and analyze the choice of the interference threshold under different traffic loads, BS distributions, and the maximum transmission power.
Minimum Enclosing Parallelogram with Outliers

We study the problem of minimum enclosing parallelogram with outliers, which asks to find, for a given set of $n$ planar points, a parallelogram with minimum area that encloses at least $(n-t)$ points, where the remaining points are regarded as outliers. We present an exact algorithm with $O(k^{2}t^{4} + n^2\log n)$ runtime and $O(kt^{2})$ space, assuming that no three points lie on the same line. Here $k=k(n,t)$ denotes the number of points on the first $(t+1)$ convex layers. We further propose an sampling algorithm with runtime $O(n+\mbox{poly}(\log{n}, t, 1/\epsilon))$, which with high probability finds a parallelogram covering at least $(1-\epsilon)(n-t)$ and at most $(n-t+1)$ points with area no more than the exact optimal value.
HeTDSE: GPU based program to solve full-dimensional-time-dependent Schrödinger equation for two-electron Helium subjected to strong laser fields

We present a GPU based openACC fortran program named HeTDSE, which provides an efficient way to investigate the non-perturbative electronic dynamics of helium subjected to a strong laser pulse by solving full-dimensional two-electron time dependent Schrodinger equation (TDSE). OpenACC is a directive-based programming model for accelerators without modifying the underlying CPU code itself. HeTDSE uses B-Spline basis sets expansion method to construct the radial part of the wavefunction, and the spherical harmonic functions is used to express for the angular part. Adams algorithm is employed for the time propagation. Our example shows HeTDSE running on an NVIDIA Kepler K20 GPU can outperform the one on an Intel E5-2640 single CPU core by a factor of 147.
Ju l 1 99 9 Architectural Considerations for Conversational Systems — The Verbmobil / INTARC Experience

Verbmobil is a large German joint research project in the area spontaneous speech-to-speech translation sytems which is sponsored by the German Federal Ministery for Research and Education. In its first phase (1992–1996) ca. 30 research groups in universities, research institutes and industry were involved, and it entered its second phase in January 1997. The overall goal is develop a system which supports face-to-face negotiation dialogues about the scheduling of meetings as its first domain, which will be enlarged to more general scenarios during the second project phase. For the dialogue situation it is assumed that two speakers with different mother tongues (German and Japanese) have some common knowledge of English. Whenever a speaker’s knowledge of English is not sufficient, the Verbmobil system will serve him as a speech translation device to which he can talk in his native language.
Efficient Learning in Large-Scale Combinatorial Semi-Bandits

We now outline the proof of Theorem 3, which is based on (Russo & Van Roy, 2013; Dani et al., 2008). LetHt denote the “history” (i.e. all the available information) by the start of episode t. Note that from the Bayesian perspective, conditioning on Ht, θ∗ and θt are i.i. d. drawn from N(θ̄t,Σt) (see (Russo & Van Roy, 2013)). This is because that conditioning on Ht, the posterior belief in θ∗ is N(θ̄t,Σt) and based on Algorithm 2, θt is independently sampled from N(θ̄t,Σt). Since ORACLE is a fixed combinatorial optimization algorithm (even though it can be independently randomized), and E,A,Φ are all fixed, then conditioning onHt, A∗ and A are also i.i. d. , furthermore, A∗ is conditionally independent of θt, and A is conditionally independent of θ∗. To simplify the exposition, ∀θ ∈ R and ∀A ⊆ E, we define
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains

Fitting high-dimensional data involves a delicate tradeoff between faithful representation and the use of sparse models. Too often, sparsity assumptions on the fitted model are too restrictive to provide a faithful representation of the observed data. In this paper, we present a novel framework incorporating sparsity in different domains.We decompose the observed covariance matrix into a sparse Gaussian Markov model (with a sparse precision matrix) and a sparse independence model (with a sparse covariance matrix). Our framework incorporates sparse covariance and sparse precision estimation as special cases and thus introduces a richer class of high-dimensional models. We characterize sufficient conditions for identifiability of the two models, \viz Markov and independence models. We propose an efficient decomposition method based on a modification of the popular $\ell_1$-penalized maximum-likelihood estimator ($\ell_1$-MLE). We establish that our estimator is consistent in both the domains, i.e., it successfully recovers the supports of both Markov and independence models, when the number of samples $n$ scales as $n = \Omega(d^2 \log p)$, where $p$ is the number of variables and $d$ is the maximum node degree in the Markov model. Our experiments validate these results and also demonstrate that our models have better inference accuracy under simple algorithms such as loopy belief propagation.
Performance of orthogonal matching pursuit for multiple measurement vectors with noise

Orthogonal matching pursuit (OMP) algorithm for the multiple measurement vectors (MMV) is a greedy method to find the sparse matrix with few nonzero rows that represents the measurement vectors under the sensing matrix. This paper analyzes the recovery performance of OMP for MMV (OMPMMV) in the bounded noise scenarios, and provides the sufficient conditions that are related to the sensing matrix and sparse matrix for exact support recovery. We start with the intuitive sufficient conditions for exact support recovery, and then apply these conditions to scenarios of two types of bounded noise. The results show that under some conditions on the coherence of the sensing matrix and the minimum ℓ2 norm of any nonzero row vector from the sparse matrix, exact support recovery of sparse matrix can be guaranteed.