Machine Learning with Limited Labeled Data 4/3/19

Apr 3, 20195 likes3,657 views

Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.

Confidential – Restricted
LEARNING with LIMITED LABELED DATA
Shioulin Sam and Nisha Muktewar
Sanjay Krishnan (University of Chicago), Ines Montani (Explosion AI)

Machine Learning with Limited Labeled Data 4/3/19

Confidential – Restricted
Choosing what to label

Confidential – Restricted 18
Random Sampling

Confidential – Restricted 19
Uncertainty - Margin Sampling

Confidential – Restricted 20
Uncertainty - Margin Sampling

Confidential – Restricted
Extending to deep learning

Confidential – Restricted 22
Distance from the decision boundary
Computing the distance between the datapoint and the closest neighbor of a different
class

Confidential – Restricted 23
Distance from the decision boundary
Using adversarial perturbations to estimate the distance
Image from https://openai.com/blog/adversarial-example-research/

Confidential – Restricted 24
Distance from the decision boundary
Computing the distance between the datapoint and the decision boundary using
perturbation magnitude

Confidential – Restricted 30
Ines Montani
Founder of Explosion AI

Confidential – Restricted 31
Sanjay Krishnan
Assistant Professor of Computer Science,
University of Chicago

The document discusses using Cloudera DataFlow to address challenges with collecting, processing, and analyzing log data across many systems and devices. It provides an example use case of logging modernization to reduce costs and enable security solutions by filtering noise from logs. The presentation shows how DataFlow can extract relevant events from large volumes of raw log data and normalize the data to make security threats and anomalies easier to detect across many machines.

Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.

The document outlines the 2021 finalists for the annual Data Impact Awards program, which recognizes organizations using Cloudera's platform and the impactful applications they have developed. It provides details on the challenges, solutions, and outcomes for each finalist project in the categories of Data Lifecycle Connection, Cloud Innovation, Data for Enterprise AI, Security & Governance Leadership, Industry Transformation, People First, and Data for Good. There are multiple finalists highlighted in each category demonstrating innovative uses of data and analytics.

2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.

Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.

Edc event vienna presentation 1 oct 2019Cloudera, Inc.

The document outlines the agenda for Cloudera's Enterprise Data Cloud event in Vienna. It includes welcome remarks, keynotes on Cloudera's vision and customer success stories. There will be presentations on the new Cloudera Data Platform and customer case studies, followed by closing remarks. The schedule includes sessions on Cloudera's approach to data warehousing, machine learning, streaming and multi-cloud capabilities.

Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.

Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.

Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.

Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.

Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.

Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.

Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 3Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 2Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 1Cloudera, Inc.

The document discusses the benefits and trends of modernizing a data warehouse. It outlines how a modern data warehouse can provide deeper business insights at extreme speed and scale while controlling resources and costs. Examples are provided of companies that have improved fraud detection, customer retention, and machine performance by implementing a modern data warehouse that can handle large volumes and varieties of data from many sources.

Extending Cloudera SDX beyond the PlatformCloudera, Inc.

Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.

Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.

Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.

Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.

Cloudera SDXCloudera, Inc.

Introducing Workload XM 8.7.18Cloudera, Inc.

Workload Experience Manager (XM) gives you the visibility necessary to efficiently migrate, analyze, optimize, and scale workloads running in a modern data warehouse. In this recorded webinar we discuss common challenges running at scale with modern data warehouse, benefits of end-to-end visibility into workload lifecycles, overview of Workload XM and live demo, real-life customer before/after scenarios, and what's next for Workload XM.

Get started with Cloudera's cyber solutionCloudera, Inc.

Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?

Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.

Cloud Data Warehousing with Cloudera Altus 7.24.18Cloudera, Inc.

How Cloudera SDX can aid GDPR complianceCloudera, Inc.

Cloudera's big data platform can help organizations comply with the EU's General Data Protection Regulation (GDPR) in three key ways: 1. It provides a single system to securely store, govern, and manage all analytic workloads and personal data across on-premises, cloud, structured, and unstructured data sources. 2. Its shared services like data catalog, security, governance, and lifecycle management can be applied uniformly across the platform to meet GDPR principles like data minimization, storage limitation, and accuracy. 3. Specific capabilities like its GDPR data hub, consent management, and ability to delete individual data records upon request help automate key GDPR requirements at scale,

When SAP alone is not enoughCloudera, Inc.

To disrupt and innovate, you need access to data. All of your data. The challenge for many organisations is that the data they need is locked away in a variety of silos. And there's perhaps no bigger silo than one of the most a widely deployed business application: SAP. Bringing together all your data for analytics and machine learning unlocks new insights and business value. Together, Cloudera and Datavard hold the key to breaking SAP data out of its silo, providing access to unlimited and untapped opportunities that currently lay hidden.

Multi task learning stepping away from narrow expert models 7.11.18Cloudera, Inc.

Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.

Exclusively through Cloudera OnDemand, Cloudera Security Training introduces you to the tools and techniques that Cloudera's solution architects use to protect the clusters our customers rely on for critical machine learning and analytics workloads. This webinar will give you a sneak peek at our new on-demand security course and show you the immense scope of Cloudera training. From authentication and authorization to encryption, auditing, and everything in between, this course gives you the skills you need to properly secure your Cloudera cluster.

Splunk Security Update | Public Sector Summit Germany 2025Splunk

SAP Modernization: Maximizing the Value of Your SAP S/4HANA Migration.pdfPrecisely

More Related Content

More from Cloudera, Inc. (20)

Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.

Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.

Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 3Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 2Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 1Cloudera, Inc.

Extending Cloudera SDX beyond the PlatformCloudera, Inc.

Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.

Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.

Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.

Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.

Cloudera SDXCloudera, Inc.

Introducing Workload XM 8.7.18Cloudera, Inc.

Get started with Cloudera's cyber solutionCloudera, Inc.

Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.

Cloud Data Warehousing with Cloudera Altus 7.24.18Cloudera, Inc.

How Cloudera SDX can aid GDPR complianceCloudera, Inc.

When SAP alone is not enoughCloudera, Inc.

Multi task learning stepping away from narrow expert models 7.11.18Cloudera, Inc.

Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.

Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.

Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.

Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 3Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 2Cloudera, Inc.

Modern Data Warehouse Fundamentals Part 1Cloudera, Inc.

Extending Cloudera SDX beyond the PlatformCloudera, Inc.

Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.

Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.

Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.

Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.

Cloudera SDXCloudera, Inc.

Introducing Workload XM 8.7.18Cloudera, Inc.

Get started with Cloudera's cyber solutionCloudera, Inc.

Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.

Cloud Data Warehousing with Cloudera Altus 7.24.18Cloudera, Inc.

How Cloudera SDX can aid GDPR complianceCloudera, Inc.

When SAP alone is not enoughCloudera, Inc.

Multi task learning stepping away from narrow expert models 7.11.18Cloudera, Inc.

Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.

Recently uploaded (20)

Splunk Security Update | Public Sector Summit Germany 2025Splunk

SAP Modernization: Maximizing the Value of Your SAP S/4HANA Migration.pdfPrecisely

Drupalcamp Finland – Measuring Front-end Energy ConsumptionExove

UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity

Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts! 📕 Agenda Welcome & Introductions Orchestrator API Overview Exploring the Swagger Interface Test Manager API Highlights Streamlining Automation & Testing with APIs (Demo) Q&A and Open Discussion Perfect for developers, testers, and automation enthusiasts! 👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/ This session streamed live on April 29, 2025, 18:00 CET. Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.

How analogue intelligence complements AIPaul Rowe

Artificial Intelligence is providing benefits in many areas of work within the heritage sector, from image analysis, to ideas generation, and new research tools. However, it is more critical than ever for people, with analogue intelligence, to ensure the integrity and ethical use of AI. Including real people can improve the use of AI by identifying potential biases, cross-checking results, refining workflows, and providing contextual relevance to AI-driven results. News about the impact of AI often paints a rosy picture. In practice, there are many potential pitfalls. This presentation discusses these issues and looks at the role of analogue intelligence and analogue interfaces in providing the best results to our audiences. How do we deal with factually incorrect results? How do we get content generated that better reflects the diversity of our communities? What roles are there for physical, in-person experiences in the digital world?

AI and Data Privacy in 2025: Global TrendsInData Labs

In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy. This infographic contains: -AI and data privacy: Key findings -Statistics on AI data privacy in the today’s world -Tips on how to overcome data privacy challenges -Benefits of AI data security investments. Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.

Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex

Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how: • Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules. • Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance. • Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity. • Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications. • Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market. With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications. Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family

Manifest Pre-Seed Update | A Humanoid OEM Deeptech In Francechb3

Build Your Own Copilot & Agents For DevsBrian McKeiver

Into The Box Conference Keynote Day 1 (ITB2025)Ortus Solutions, Corp

Generative Artificial Intelligence (GenAI) in BusinessDr. Tathagat Varma

Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell

Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company

Explore the benefits and features of advanced logistics management software for businesses in Riyadh. This guide delves into the latest technologies, from real-time tracking and route optimization to warehouse management and inventory control, helping businesses streamline their logistics operations and reduce costs. Learn how implementing the right software solution can enhance efficiency, improve customer satisfaction, and provide a competitive edge in the growing logistics sector of Riyadh.

TrsLabs - Fintech Product & Business ConsultingTrs Labs

Hybrid Growth Mandate Model with TrsLabs Strategic Investments, Inorganic Growth, Business Model Pivoting are critical activities that business don't do/change everyday. In cases like this, it may benefit your business to choose a temporary external consultant. An unbiased plan driven by clearcut deliverables, market dynamics and without the influence of your internal office equations empower business leaders to make right choices. Getting things done within a budget within a timeframe is key to Growing Business - No matter whether you are a start-up or a big company Talk to us & Unlock the competitive advantage

The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john

HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda

Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/ HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client. Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience. In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including - Accessing the console - Locating and interpreting log files - Accessing the data folder within the browser’s cache (using OPFS) - Understand the difference between single- and multi-user scenarios - Utilizing Client Clocking

What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat

The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.

2025-05-Q4-2024-Investor-Presentation.pptxSamuele Fogagnolo

Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok

Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies

Splunk Security Update | Public Sector Summit Germany 2025Splunk

SAP Modernization: Maximizing the Value of Your SAP S/4HANA Migration.pdfPrecisely

Drupalcamp Finland – Measuring Front-end Energy ConsumptionExove

UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity

How analogue intelligence complements AIPaul Rowe

AI and Data Privacy in 2025: Global TrendsInData Labs

Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex

Manifest Pre-Seed Update | A Humanoid OEM Deeptech In Francechb3

Build Your Own Copilot & Agents For DevsBrian McKeiver

Into The Box Conference Keynote Day 1 (ITB2025)Ortus Solutions, Corp

Generative Artificial Intelligence (GenAI) in BusinessDr. Tathagat Varma

Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell

Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company

TrsLabs - Fintech Product & Business ConsultingTrs Labs

The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john

HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda

What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat

2025-05-Q4-2024-Investor-Presentation.pptxSamuele Fogagnolo

Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok

Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies

Machine Learning with Limited Labeled Data 4/3/19

1. Confidential – Restricted LEARNING with LIMITED LABELED DATA Shioulin Sam and Nisha Muktewar Sanjay Krishnan (University of Chicago), Ines Montani (Explosion AI)

3. Confidential – Restricted 3

4. Confidential – Restricted 4

5. Confidential – Restricted 5

6. Confidential – Restricted 6

7. Confidential – Restricted 7

8. Confidential – Restricted 8

9. Confidential – Restricted 9

10. Confidential – Restricted 10

11. Confidential – Restricted 11

12. Confidential – Restricted 12

13. Confidential – Restricted 13

14. Confidential – Restricted 14

15. Confidential – Restricted 15

16. Confidential – Restricted 16

17. Confidential – Restricted Choosing what to label

18. Confidential – Restricted 18 Random Sampling

19. Confidential – Restricted 19 Uncertainty - Margin Sampling

20. Confidential – Restricted 20 Uncertainty - Margin Sampling

21. Confidential – Restricted Extending to deep learning

22. Confidential – Restricted 22 Distance from the decision boundary Computing the distance between the datapoint and the closest neighbor of a different class

23. Confidential – Restricted 23 Distance from the decision boundary Using adversarial perturbations to estimate the distance Image from https://openai.com/blog/adversarial-example-research/

24. Confidential – Restricted 24 Distance from the decision boundary Computing the distance between the datapoint and the decision boundary using perturbation magnitude

25. Confidential – Restricted Demo

26. Confidential – Restricted 26

27. Confidential – Restricted 27

28. Confidential – Restricted 28

29. Confidential – Restricted 29

30. Confidential – Restricted 30 Ines Montani Founder of Explosion AI

31. Confidential – Restricted 31 Sanjay Krishnan Assistant Professor of Computer Science, University of Chicago

32. Confidential – Restricted 32 Q & A

33. Confidential – Restricted THANK YOU

34. Confidential – Restricted 34

35. Confidential – Restricted 35

36. Confidential – Restricted 36