An Efficient Threshold-Driven Aggregate-Label Learning Algorithm for Multimodal Information Processing

The aggregate-label learning paradigm tackles the long-standing temporary credit assignment (TCA) problem in neuroscience and machine learning, enabling spiking neural networks to learn multimodal sensory clues with delayed feedback signals. However, the existing aggregate-label learning algorithms only work for single spiking neurons, and with low learning efficiency, which limit their real-world applicability. To address these limitations, we first propose an efficient threshold-driven plasticity algorithm for spiking neurons, namely ETDP. It enables spiking neurons to generate the desired number of spikes that match the magnitude of delayed feedback signals and to learn useful multimodal sensory clues embedded within spontaneous spiking activities. Furthermore, we extend the ETDP algorithm to support multi-layer spiking neural networks (SNNs), which significantly improves the applicability of aggregate-label learning algorithms. We also validate the multi-layer ETDP learning algorithm in a multimodal computation framework for audio-visual pattern recognition. Experimental results on both synthetic and realistic datasets show significant improvements in the learning efficiency and model capacity over the existing aggregate-label learning algorithms. It, therefore, provides many opportunities for solving real-world multimodal pattern recognition tasks with spiking neural networks

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic signal control poses its unique challenges for reinforcement learning in terms of adapting to dynamic traffic environment and coordinating thousands of agents including vehicles and pedestrians. A key factor in the success of modern reinforcement learning relies on a good simulator to generate a large number of data samples for learning. The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios. This motivates us to create a new traffic simulator CityFlow with fundamentally optimized data structures and efficient algorithms. CityFlow can support flexible definitions for road network and traffic flow based on synthetic and real-world data. It also provides user-friendly interface for reinforcement learning. Most importantly, CityFlow is more than twenty times faster than SUMO and is capable of supporting city-wide traffic simulation with an interactive render for monitoring. Besides traffic signal control, CityFlow could serve as the base for other transportation studies and can create new possibilities to test machine learning methods in the intelligent transportation domain.Comment: WWW 2019 Demo Pape

Electroplating lithium transition metal oxides.

Materials synthesis often provides opportunities for innovation. We demonstrate a general low-temperature (260°C) molten salt electrodeposition approach to directly electroplate the important lithium-ion (Li-ion) battery cathode materials LiCoO2, LiMn2O4, and Al-doped LiCoO2. The crystallinities and electrochemical capacities of the electroplated oxides are comparable to those of the powders synthesized at much higher temperatures (700° to 1000°C). This new growth method significantly broadens the scope of battery form factors and functionalities, enabling a variety of highly desirable battery properties, including high energy, high power, and unprecedented electrode flexibility

Expressionism in furniture

In the first 25 years of my life, I always thought I was a free man, I followed my passion to choose art and design as my career, and strived to enter the best design school. However, until I moving to Providence, and fished on a beach over the midnight, I finally realized, actually I am the victim in dilemma who is always paralyzed by the standards we created. In that midnight, I realized time is not only a number, it can be the track of galaxy or the fluctuation of tide. And I introspected myself why my schools are the best, just because people defined they are? Did I contemplate about whether they are the most suitable for me? The answer is clear, I always follow suit which is defined by other people, and actually I don’t have my own judgment, I’m living in standards we created. But, I’m lucky, at last, I realize it. Most of time, we need to ‘See through the appearance to perceive the essence’, find the truth which belongs to ourselves. Just like Expressionism, artists create projects to express emotion through abundant color and exaggerated figure rather than depicting objective things. We need to directly rethink the essence of our world without any appearances

Self-Effacement in Christian Mysticism: A Case Study of Teresa of Ávila and Simone Weil

The neoliberal society we live in encourages a constant maximization of the “project of the self.” The tradition of Christian mysticism, centered on self-denial and passivity, provides an alternative understanding of the self. In this essay, I draw testimonial and theoretical accounts of mysticism from the autobiography of a 16th-century Spanish nun, Teresa of Ávila, and essays from a 20th-century French philosopher, Simone Weil. By bringing these two authors in conversation, I hope to illuminate three aspects of self-effacement in the Christian mystical tradition. I first start with discussing the idea of labor as a means to prepare for self-annihilation by rendering the self porous through trauma, which heightens the self’s awareness of its own limit and dependence. The second section argues that the crux of Teresa and Weil’s self-effacement lies in their understanding of Christ’s incarnation and a desire to imitate him. This is done through identifying with Christ’s suffering body or mirroring Christ’s relinquishment of divinity to descend into the human world. Lastly, I explore apophatic language as a suitable mode of representing self-effacement. Teresa and Weil’s use of apophatic language reflects an understanding of God as something beyond the capacity of human intellect and justifies their desire in passively receiving the divine. Throughout this essay, I critically examine the notion of passivity both as internalized by these two mystics as well as sometimes performative and constructed

Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes

We develop several provably efficient model-free reinforcement learning (RL) algorithms for infinite-horizon average-reward Markov Decision Processes (MDPs). We consider both online setting and the setting with access to a simulator. In the online setting, we propose model-free RL algorithms based on reference-advantage decomposition. Our algorithm achieves $\widetilde{O}(S^5A^2\mathrm{sp}(h^*)\sqrt{T})$ regret after $T$ steps, where $S\times A$ is the size of state-action space, and $\mathrm{sp}(h^*)$ the span of the optimal bias function. Our results are the first to achieve optimal dependence in $T$ for weakly communicating MDPs. In the simulator setting, we propose a model-free RL algorithm that finds an $\epsilon$-optimal policy using $\widetilde{O} \left(\frac{SA\mathrm{sp}^2(h^*)}{\epsilon^2}+\frac{S^2A\mathrm{sp}(h^*)}{\epsilon} \right)$ samples, whereas the minimax lower bound is $\Omega\left(\frac{SA\mathrm{sp}(h^*)}{\epsilon^2}\right)$. Our results are based on two new techniques that are unique in the average-reward setting: 1) better discounted approximation by value-difference estimation; 2) efficient construction of confidence region for the optimal bias function with space complexity $O(SA)$

Correlation between Parenting Styles and Learning Stress Junior High School Chinese class Students in Zibo City, China

In this study, we investigate the significance of parenting styles in the educational development of junior high school students, recognizing the vital role of family education during this formative period. As the primary educators of their children, parents wield considerable influence on their offspring’s lives, with family education offering distinct advantages over other forms of education. The status and role of family education remain undisputed. Parenting styles encompass a combination of upbringing concepts, behaviors, and emotional expressions toward children. We examine the characteristics and determining factors of different parenting styles, focusing on three typical family upbringing patterns: authoritative, Authoritarian, and democratic. Additionally, we explore the significant impact of these diverse parenting styles on students’ stress levels related to learning Chinese. The paper delves into the essential role of effective and suitable parenting styles in fostering comprehensive and healthy development in students. Furthermore, we elucidate the strategies and methods for establishing positive parenting styles. This quantitative correlational research involved a random sample of 330 participants, collected from three junior middle schools in Zibo City. Utilizing SPSS, we analyzed the relationship between parenting styles and Chinese learning stress among junior high school student