generated subquery results maximum

CF1201C - Maximum Median

思路 二分答案。对于一个mid,查询中位数要是为mid的话至少要做多少次操作,最小操作次数就是排序后从中位数开始计算max(0, mid - v[i])的和 ac代码 #include <bits/stdc++.h> using namespace std; using i64 = long lon ......
Maximum Median 1201C 1201 CF

mybatis-generator:generate生成器将另外的数据库内同名表生成

问题: 在使用mybatis-generator:generate生成器时,会生成别的数据库内同表名; 因为是相同表名。 解决: 在生成器的配置文件中的数据库连接地址内添加: <!--放置生成其他库同名表--> <property name="nullCatalogMeansCurrent" val ......

[论文阅读] Self-conditioned Image Generation via Generating Representations

Pre title: Self-conditioned Image Generation via Generating Representations accepted: arXiv 2023 paper: https://arxiv.org/abs/2312.03701 code: https:/ ......

[转帖]ORA-01450 maximum key length (3215) exceeded

https://blog.csdn.net/Hehuyi_In/article/details/106579031 一、 问题背景 给一个业务表online建索引时遇到了ORA-01450 maximum key length (3215) exceeded报错,看字面意思是字段太长了,检查表字段类 ......
exceeded maximum length 01450 3215

Maximum Depth of Binary Tree

Source Problem Given a binary tree, find its maximum depth. The maximum depth is the number of nodes along the longest path from the rootnode down to ......
Maximum Binary Depth Tree of

开课吧前端1期.阶段5:generator,模块化与babel

复习:ES6 变量let、箭头function、参数等、map、reduce、filter、forEach Promise消除回调,Promise.all([p1,p2,p3]).then() 单独Promise并不能帮我们解决所有问题,还有2个兄弟是从Promise过度出来的,generator ......
前端 generator 模块 阶段 babel

《A Novel Table-to-Graph Generation Approach for Document-Level Joint Entity and Relation Extraction》阅读笔记

代码 原文地址 文档级关系抽取(DocRE)的目的是从文档中提取实体之间的关系,这对于知识图谱构建等应用非常重要。然而,现有的方法通常需要预先识别出文档中的实体及其提及,这与实际应用场景不一致。为了解决这个问题,本文提出了一种新颖的表格到图生成模型(TAG),它能够在文档级别上同时抽取实体和关系。T ......

Maximum And Queries (hard version)

题目传送门 感觉这题比 \(\rm F\) 难啊,\(\rm F\) 就是个板子,但为啥这题是蓝的,\(\rm F\) 是紫的。 思路 首先考虑 \(nq\) 怎么做。 发现很简单,按位贪心就行了。 具体地说,从大到小枚举二进制位,判断答案中能否出现这一位,若 \(i\) 当前这一位没有值,那么必须 ......
Maximum Queries version hard And

ICPC2021Kunming G Find the Maximum 题解

Question Find the Maximum 给出一个树,每个点有一个权值 \(b_n\),求一条树上路径 \(V\),要求 \(\frac{\sum_{u\in V (-x^2+b_u x)}}{|V|}\) 最大,其中 \(x\) 是自己选择的一个树 Solution 先转化一下 \(\f ......
题解 Kunming Maximum ICPC 2021

python生成器generator的用法

通过列表生成式,我们可以直接创建一个列表。但是,受到内存限制,列表容量肯定是有限的。而且,创建一个包含100万个元素的列表,不仅占用很大的存储空间,如果我们仅仅需要访问前面几个元素,那后面绝大多数元素占用的空间都白白浪费了。 所以,如果列表元素可以按照某种算法推算出来,那我们是否可以在循环的过程中不 ......
生成器 generator python

GPT-1论文《Improving Language Understanding by Generative Pre-Training》解读

背景 GPT-1 采用了两阶段训练的方式: 1. 第一阶段 pre-training,在海量文本上训练,无需label,根据前k-1个词预测第k个单词是什么,第一阶段的训练让模型拥有了很多的先验知识,模型具有非常强的泛化性 2. 第二阶段在特定任务上fine-tuning,让模型能适应不同的任务,提 ......

POLIR-Int-Generative AI in 2024: The 6 most important consumer tech trends for next year

Generative AI in 2024: The 6 most important consumer tech trends for next year Qualcomm executives reveal key trends in AI, consumer technology and mo ......

Generative AI generates tricky choices for managers

Generative AI generates tricky choices for managers Transformational technologies can be very trying THE REMARKABLE capabilities of generative artific ......
Generative generates managers choices tricky

[论文阅读] Learning Component-Level and Inter-Class Glyph Representation for few-shot Font Generation

Pre title: Learning Component-Level and Inter-Class Glyph Representation for few-shot Font Generation accepted: ICME 2023 paper: https://ieeexplore.ie ......

CF1881F Minimum Maximum Distance 题解

因为白点对 \(f_i\) 没有贡献,所以可以重构出一棵原树的子树,使得所有的叶子都为标记点且标记点数量不变(没有删去标记点)。因为没有标记被删去且结构不变,所以这棵树的答案与原树答案相同。 现在,对于所有节点,到它距离最大的标记点一定在叶子上。那么问题就变为:求出树上任意一点到所有叶子节点的最大距 ......
题解 Distance Minimum Maximum 1881F

Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached

一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......

论文阅读-Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks

1. GARF 简介 代码地址:https://github.com/PJinfeng/Garf-master 基于 SeqGAN 提出了一种自监督、数据驱动的数据清洗框架——GARF。 GARF 的数据清洗分为两个步骤: 规则生成 (Rule generation with SeqGAN):利用 ......

Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached

一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......

Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached

一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......

Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached

一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......

Deformable ConvNets V2: More Deformable, Better Results 可变形卷积v2

Deformable ConvNets V2: More Deformable, Better Results * Authors: [[Xizhou Zhu]], [[Han Hu]], [[Stephen Lin]], [[Jifeng Dai]] DOI: 10.1109/CVPR.2019. ......
Deformable 卷积 ConvNets Results Better

Django报错UnorderedObjectListWarning: Pagination may yield inconsistent results with an unordered object_list

Django报错UnorderedObjectListWarning: Pagination may yield inconsistent results with an unordered object_list 报错 报错信息如下: Django报错Django报错UnorderedObject ......

Ansor:Generating High-Performance Tensor Program for Deep Learning

Ansor:Generating High-Performance Tensor Program for Deep Learning Abstract 高性能的张量程序对于保证深度神经网络的高效执行十分关键,但是在不同硬件平台上获取高性能的张量程序并不容易。近年的研究中,深度学习系统依赖硬件供应商提 ......

generative AI

Welcome to generative AI for everyone. Since the release of ChatGPT, AI specifically, generative AI has caught the attention of many individuals, corp ......
generative AI

Generative AI: Friend or Foe?

Generative AI: Friend or Foe? Introduction Artificial intelligence (AI) is rapidly changing the world around us, and the writing and publishing indust ......
Generative Friend Foe AI or

【论文阅读笔记】【多模态-Vision-Language Pretraining】 BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

BLIP ICML 2022 (Spotlight) 读论文思考的问题 论文试图解决什么问题?写作背景是什么? 问题: 在视觉-语言预训练(VLP)中,如何更加高效地利用充斥着噪声的海量图文对数据,提升预训练效果? 如何设计模型,使得预训练后的模型在理解(understanding-based)任务 ......

The numerical results

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numerical results The

GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models

前置知识:【EM算法深度解析 - CSDN App】http://t.csdnimg.cn/r6TXM Motivation 目前的语义分割通常采用判别式分类器,然而这存在三个问题:这种方式仅仅学习了决策边界,而没有对数据分布进行建模;每个类仅学习一个向量,没有考虑到类内差异;OOD数据效果不好。生 ......

Class-Incremental Learning with Generative Classifiers(CVPR2021W)

前置知识:VAE(可以参考https://zhuanlan.zhihu.com/p/348498294) Motivation 之前的方法通常使用判别式分类器,对条件分布\(p(y|\textbf{x})\)进行建模(classifier+softmax+ce)。其问题在于分类器会偏向最新学的类别, ......

MemGPT中_generate_reply_for_user_message报错TypeError: cannot unpack non-iterable coroutine object

memgpt/autogen/memgpt_agent.py", line 230, in _generate_reply_for_user_message (TypeError: cannot unpack non-iterable coroutine object 解决 将memgpt/auto ......
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