A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
AnChain.AI detects NFT wash trading with 0.14% of transactions flagged.
This work learns visual representations for deformable objects using contrastive estimation.
Collectives can manipulate learning platforms by coordinated data submission, requiring strategic assessments and algorithms.
This paper improves self-play learning in games by manipulating experience distributions.
Robotic clothing manipulation improved with fashion image analysis techniques.
In this paper, we introduce an unsupervised learning approach to automatically discover, summarize, and manipulate artistic styles from large collections of paintings. Our method is based on archetypal analysis, which is an unsupervised learning technique akin to sparse coding with a geometric interpretation. When appl…
We address the collective matrix completion problem of jointly recovering a collection of matrices with shared structure from partial (and potentially noisy) observations. To ensure well--posedness of the problem, we impose a joint low rank structure, wherein each component matrix is low rank and the latent space of th…
A Markov-chain model is developed for the purpose estimation of the cure rate of non-performing loans. The technique is performed collectively, on portfolios and it can be applicable in the process of calculation of credit impairment. It is efficient in terms of data manipulation costs which makes it accessible even to…
P3I learns holistic scene representations from a single image.
Study shows small groups can influence machine learning algorithms.
Motion planning and control are key problems in a collection of robotic applications including the design of autonomous agile vehicles and of minimalist manipulators. These problems can be accurately formalized within the language of affine connections and of geometric control theory. In this paper we overview recent r…
This work tackles real-world robotic reinforcement learning challenges.
For a rational homology 3-sphere with a $\spinc$ structure $\s$, we show that simple algebraic manipulations of our construction of equivariant Seiberg-Witten Floer homology lead to a collection of variants which are topological invariants. We establish exact sequences relating them, we show that they satisfy a dua…
We develop dependent hierarchical normalized random measures and apply them to dynamic topic modeling. The dependency arises via superposition, subsampling and point transition on the underlying Poisson processes of these measures. The measures used include normalised generalised Gamma processes that demonstrate power …
AI learns market manipulation through simulation, suggesting regulation.
The paper analyzes how leverage affects manipulation in event-linked markets, offering new insights into regulation.
New model improves neural network robustness against input manipulations.
New method learns various data manipulation schemes for model training.
New approach for deep neural networks to learn invariance through adversarial forgetting.
This paper studies poisoning attacks in episodic RL and discovers their effectiveness depends on reward bounds.
Manipulating video content is easier than ever. Due to the misuse potential of manipulated content, multiple detection techniques that analyze the pixel data from the videos have been proposed. However, clever manipulators should also carefully forge the metadata and auxiliary header information, which is harder to do …
In this work we propose a model that can manipulate individual visual attributes of objects in a real scene using examples of how respective attribute manipulations affect the output of a simulation. As an example, we train our model to manipulate the expression of a human face using nonphotorealistic 3D renders of a f…
Prediction markets can be manipulated by traders who can move contract settlements, harming price discovery.
DIGIT is a low-cost tactile sensor for in-hand manipulation.
In Reinforcement Learning (RL), an agent explores the environment and collects trajectories into the memory buffer for later learning. However, the collected trajectories can easily be imbalanced with respect to the achieved goal states. The problem of learning from imbalanced data is a well-known problem in supervised…
Volunteer labor can temporarily yield lower benefits to charities than its costs. In such instances, organizations may wish to defer volunteer donations to a later date. Exploiting a discontinuity in blood donations' eligibility criteria, we show that deferring donors reduces their future volunteerism. In our setting, …
We present an adversarial active exploration for inverse dynamics model learning, a simple yet effective learning scheme that incentivizes exploration in an environment without any human intervention. Our framework consists of a deep reinforcement learning (DRL) agent and an inverse dynamics model contesting with each …
Paper presents a new port-Hamiltonian model for vehicle manipulators.
Optimal benchmark design varies based on costs in financial manipulation.
Study examines reasons for Nutek India's share price drop.
The paper discusses decades of stock market manipulation and its benefits.
Vision and learning have made significant progress that could improve robotics policies for complex tasks and environments. Learning deep neural networks for image understanding, however, requires large amounts of domain-specific visual data. While collecting such data from real robots is possible, such an approach lim…
New method uses statistical physics to detect financial market manipulation.
Option discovery and skill acquisition frameworks are integral to the functioning of a Hierarchically organized Reinforcement learning agent. However, such techniques often yield a large number of options or skills, which can potentially be represented succinctly by filtering out any redundant information. Such a reduc…
Market manipulation is a strategy used by traders to alter the price of financial securities. One type of manipulation is based on the process of buying or selling assets by using several trading strategies, among them spoofing is a popular strategy and is considered illegal by market regulators. Some promising tools h…
New method learns robot skills from data, matching or outperforming existing methods.
New foundation for Shapley value immune to coalitional manipulations.
Framework detects covert financial market manipulation using LOB representations.
Study reveals widespread manipulation of meme coins, leading to significant economic losses.
This paper focuses on an extension of the Limit Order Book (LOB) model with general shape introduced by Alfonsi, Fruth and Schied. Here, the additional feature allows a time-varying LOB depth. We solve the optimal execution problem in this framework for both discrete and continuous time strategies. This gives in partic…
A novel RL approach learns robotic manipulation without human demonstrations.
A new method for robot manipulation tasks using imagined object goals.
This work tackles force control for contact-rich manipulation tasks with rigid robots using RL.
Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a tradi…
Study on costs of manipulating AMM-based price oracles.
Proposes a simple method to represent and manipulate concepts using polynomials and moment statistics.
Many problems in image processing and computer vision (e.g. colorization, style transfer) can be posed as 'manipulating' an input image into a corresponding output image given a user-specified guiding signal. A holy-grail solution towards generic image manipulation should be able to efficiently alter an input image wit…
Investigates optimal execution under time-varying liquidity, preventing price manipulation.