Search Results for author: Aditya Kusupati

Found 11 papers, 7 papers with code

Matryoshka Representations for Adaptive Deployment

1 code implementation26 May 2022 Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, KaiFeng Chen, Sham Kakade, Prateek Jain, Ali Farhadi

The flexibility within the learned Matryoshka Representations offer: (a) up to 14x smaller embedding size for ImageNet-1K classification at the same level of accuracy; (b) up to 14x real-world speed-ups for large-scale retrieval on ImageNet-1K and 4K; and (c) up to 2% accuracy improvements for long-tail few-shot classification, all while being as robust as the original representations.

Ranked #20 on Image Classification on ObjectNet (using extra training data)

Image Classification Representation Learning

Disrupting Model Training with Adversarial Shortcuts

no code implementations ICML Workshop AML 2021 Ivan Evtimov, Ian Covert, Aditya Kusupati, Tadayoshi Kohno

When data is publicly released for human consumption, it is unclear how to prevent its unauthorized usage for machine learning purposes.

BIG-bench Machine Learning Image Classification

LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes

1 code implementation NeurIPS 2021 Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham Kakade, Ali Farhadi

We further quantitatively measure the quality of our codes by applying it to the efficient image retrieval as well as out-of-distribution (OOD) detection problems.

Image Retrieval OOD Detection

FLUID: A Unified Evaluation Framework for Flexible Sequential Data

1 code implementation6 Jul 2020 Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi

To foster research towards the goal of general ML methods, we introduce a new unified evaluation framework - FLUID (Flexible Sequential Data).

Continual Learning Representation Learning +1

Extreme Regression for Dynamic Search Advertising

no code implementations15 Jan 2020 Yashoteja Prabhu, Aditya Kusupati, Nilesh Gupta, Manik Varma

This paper also introduces a (3) new labelwise prediction algorithm in XReg useful for DSA and other recommendation tasks.

One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification

1 code implementation6 Sep 2019 Dhrubojyoti Roy, Sangeeta Srivastava, Aditya Kusupati, Pranshu Jain, Manik Varma, Anish Arora

Edge sensing with micro-power pulse-Doppler radars is an emergent domain in monitoring and surveillance with several smart city applications.

Feature Engineering General Classification

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network

1 code implementation NeurIPS 2018 Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma

FastRNN addresses these limitations by adding a residual connection that does not constrain the range of the singular values explicitly and has only two extra scalar parameters.

Action Classification Speech Recognition +1

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