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Robust and Private Learning of Halfspaces
In this work, we study the trade-off between differential privacy and ad...
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Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
A key factor in the success of deep neural networks is the ability to sc...
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Concept Bottleneck Models
We seek to learn models that we can interact with using high-level conce...
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Robot Object Retrieval with Contextual Natural Language Queries
Natural language object retrieval is a highly useful yet challenging tas...
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Delegated Proof of Reputation: a novel Blockchain consensus
Consensus mechanism is the heart of any blockchain network. Many project...
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Analyzing Social Media Data to Understand Consumers' Information Needs on Dietary Supplements
Despite the high consumption of dietary supplements (DS), there are not ...
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Grounding Language Attributes to Objects using Bayesian Eigenobjects
We develop a system to disambiguate objects based on simple physical des...
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Planning with State Abstractions for Non-Markovian Task Specifications
Often times, we specify tasks for a robot using temporal language that c...
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Predicting Inpatient Discharge Prioritization With Electronic Health Records
Identifying patients who will be discharged within 24 hours can improve ...
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A Fully Private Pipeline for Deep Learning on Electronic Health Records
We introduce an end-to-end private deep learning framework, applied to t...
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