19 citations · 61 across the 10 of their papers we have counts for
10 papers
Understanding and Improving the Role of Projection Head in Self-Supervised Learning
Kartik Gupta, Thalaiyasingam Ajanthan, Anton van den Hengel +1
Self-supervised learning (SSL) aims to produce useful feature representations without access to any human-labeled data annotations. Due to the success of recent SSL methods based o…
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices
Kartik Gupta, Marios Fournarakis, Matthias Reisser +2
Federated Learning (FL) is a machine learning paradigm to distributively learn machine learning models from decentralized data that remains on-device. Despite the success of standa…
Post-hoc Calibration of Neural Networks by g-Layers
Amir Rahimi, Thomas Mensink, Kartik Gupta +3
Calibration of neural networks is a critical aspect to consider when incorporating machine learning models in real-world decision-making systems where the confidence of decisions a…
Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan +3
Calibrating neural networks is of utmost importance when employing them in safety-critical applications where the downstream decision making depends on the predicted probabilities.…
Improved Gradient based Adversarial Attacks for Quantized Networks
Kartik Gupta, Thalaiyasingam Ajanthan
Neural network quantization has become increasingly popular due to efficient memory consumption and faster computation resulting from bitwise operations on the quantized networks.…
Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr +2
Quantizing large Neural Networks (NN) while maintaining the performance is highly desirable for resource-limited devices due to reduced memory and time complexity. It is usually fo…
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation
Kartik Gupta, Lars Petersson, Richard Hartley
We present a new approach for a single view, image-based object pose estimation. Specifically, the problem of culling false positives among several pose proposal estimates is addre…
Classifying Object Manipulation Actions based on Grasp-types and Motion-Constraints
Kartik Gupta, Darius Burschka, Arnav Bhavsar
In this work, we address a challenging problem of fine-grained and coarse-grained recognition of object manipulation actions. Due to the variations in geometrical and motion constr…
Nearly-optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain
In this paper, we consider the problem of Robust Matrix Completion (RMC) where the goal is to recover a low-rank matrix by observing a small number of its entries out of which a fe…
Lexical State Analyzer
Kartik Gupta, V. Krishna Nandivada
Lexical states provide a powerful mechanism to scan regular expressions in a context sensitive manner. At the same time, lexical states also make it hard to reason about the correc…