---
license: mit
task_categories:
- text-classification
tags:
- AI
- ICML
- ICML2023
---
## ICML 2023 International Conference on Machine Learning 2023 Accepted Paper Meta Info Dataset

This dataset is collect from the ICML 2024 OpenReview website (https://openreview.net/group?id=ICML.cc/2023/Conference#tab-accept-oral) as well as the arxiv website DeepNLP paper arxiv (http://www.deepnlp.org/content/paper/icml2023). For researchers who are interested in doing analysis of ICML 2023 accepted papers and potential trends, you can use the already cleaned up json files. 
Each row contains the meta information of a paper in the ICML 2023 conference. To explore more AI & Robotic papers (NIPS/ICML/ICLR/IROS/ICRA/etc) and AI equations, feel free to navigate the Equation Search Engine (http://www.deepnlp.org/search/equation) as well as the AI Agent Search Engine to find the deployed AI Apps and Agents (http://www.deepnlp.org/search/agent) in your domain. 


### Meta Information of Json File

```
{
    "abs": "https://proceedings.mlr.press/v202/aamand23a.html",
    "Download PDF": "https://proceedings.mlr.press/v202/aamand23a/aamand23a.pdf",
    "OpenReview": "https://openreview.net/forum?id=BVomXLJQoH",
    "title": "Data Structures for Density Estimation",
    "url": "https://proceedings.mlr.press/v202/aamand23a.html",
    "authors": "Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal",
    "detail_url": "https://proceedings.mlr.press/v202/aamand23a.html",
    "tags": "ICML 2023",
    "abstract": "We study statistical/computational tradeoffs for the following density estimation problem: given $k$ distributions $v_1, \\ldots, v_k$ over a discrete domain of size $n$, and sampling access to a distribution $p$, identify $v_i$ that is \"close\" to $p$. Our main result is the first data structure that, given a sublinear (in $n$) number of samples from $p$, identifies $v_i$ in time sublinear in $k$. We also give an improved version of the algorithm of Acharya et al. (2018) that reports $v_i$ in time linear in $k$. The experimental evaluation of the latter algorithm shows that it achieves a significant reduction in the number of operations needed to achieve a given accuracy compared to prior work."
}

```



## Related

## AI Equation
[List of AI Equations and Latex](http://www.deepnlp.org/equation/category/ai) <br>
[List of Math Equations and Latex](http://www.deepnlp.org/equation/category/math) <br>
[List of Physics Equations and Latex](http://www.deepnlp.org/equation/category/physics) <br>
[List of Statistics Equations and Latex](http://www.deepnlp.org/equation/category/statistics) <br>
[List of Machine Learning Equations and Latex](http://www.deepnlp.org/equation/category/machine%20learning) <br>

## AI Agent Marketplace and Search
[AI Agent Marketplace and Search](http://www.deepnlp.org/search/agent) <br>
[Robot Search](http://www.deepnlp.org/search/robot) <br>
[Equation and Academic search](http://www.deepnlp.org/search/equation) <br>
[AI & Robot Comprehensive Search](http://www.deepnlp.org/search) <br>
[AI & Robot Question](http://www.deepnlp.org/question) <br>
[AI & Robot Community](http://www.deepnlp.org/community) <br>
[AI Agent Marketplace Blog](http://www.deepnlp.org/blog/ai-agent-marketplace-and-search-portal-reviews-2025) <br>

## AI Agent Reviews
[AI Agent Marketplace Directory](http://www.deepnlp.org/store/ai-agent) <br>
[Microsoft AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-microsoft-ai-agent) <br>
[Claude AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-claude-ai-agent) <br>
[OpenAI AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-openai-ai-agent) <br>
[Saleforce AI Agents Reviews](http://www.deepnlp.org/store/pub/pub-salesforce-ai-agent) <br>
[AI Agent Builder Reviews](http://www.deepnlp.org/store/ai-agent/ai-agent-builder) <br>