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  1. Neural networks made easy (Part 61): Optimism issue in offline reinforcement learning

    by , Yesterday at 11:58 AM
    Recently, offline reinforcement learning methods have become widespread, which promises many prospects in solving problems of varying complexity. However, one of the main problems that researchers face is the optimism that can arise while learning. The agent optimizes its strategy based on the data from the training set and gains confidence in its actions. But the training set is quite often not able to cover the entire variety of possible states and transitions of the environment. In a stochastic
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  2. Neural networks made easy (Part 74): Trajectory prediction with adaptation

    by , Yesterday at 07:05 AM
    Building a trading strategy is inseparable from analyzing the market situation and forecasting the most likely movement of a financial instrument. This movement often correlated with other financial assets and macroeconomic indicators. This can be compared with the movement of transport, where each vehicle follows its own individual destination. However, their actions on the road are interconnected to a certain extent and are strictly regulated by traffic rules. Also, due to the individual perception
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  3. Civilization VII, Black Myth Wukong and Other Trailers at Summer Game Fest Showcase

    by , Yesterday at 05:52 AM
    To kick off Summer Game Fest, the ringleader of the successor to E3, Geoff Keighley, showcased a set of game trailers for games we've heard of and others debuting for the first time.
    While Microsoft, Sony and Nintendo have trended toward their own showcases, with E3 gone, Summer Game Fest has become the big mid-year multi-platform release show. And this year, we saw a huge selection of games big and small in the two-hour showcase.

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  4. Causal inference in time series classification problems

    by , 06-14-2024 at 07:20 PM
    In the previous article, we have thoroughly examined training via meta learner and cross-validation, as well as saving models in the ONNX format. I have also noted that machine learning models are not capable of finding patterns out of the box in disparate and contradictory data. In this case, it is very important what exactly is sent to the input and output of a neural network or any other machine learning algorithm.

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    This article describes an attempt to understand
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  5. Pair trading

    by , 06-10-2024 at 11:26 AM
    Currently, there are a huge number of trading strategies for every taste. All these strategies are aimed at making a profit. But making a profit is in one way or another connected with the risks - the greater the expected profit, the higher the risks. A logical question arises: is it possible to reduce trading risks to a minimum, while receiving small but stable profits? These conditions are met by pair trading.

    Pair trading is a variery of statistical arbitrage first proposed
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