no code implementations • 20 Mar 2023 • Xuxin Cheng, Ashish Kumar, Deepak Pathak
Locomotion has seen dramatic progress for walking or running across challenging terrains.
no code implementations • 16 Dec 2022 • Ashish Kumar, Ilya Kuzovkin
Although offline learning techniques can learn from data generated by a sub-optimal behavior agent, there is still an opportunity to improve the sample complexity of existing offline reinforcement learning algorithms by strategically introducing human demonstration data into the training process.
no code implementations • 14 Nov 2022 • Ananye Agarwal, Ashish Kumar, Jitendra Malik, Deepak Pathak
Animals are capable of precise and agile locomotion using vision.
no code implementations • 7 Nov 2022 • Antonio Loquercio, Ashish Kumar, Jitendra Malik
In this work, we show how to learn a visual walking policy that only uses a monocular RGB camera and proprioception.
1 code implementation • 10 Oct 2022 • Haozhi Qi, Ashish Kumar, Roberto Calandra, Yi Ma, Jitendra Malik
Generalized in-hand manipulation has long been an unsolved challenge of robotics.
no code implementations • 19 Sep 2022 • Dingqi Zhang, Antonio Loquercio, Xiangyu Wu, Ashish Kumar, Jitendra Malik, Mark W. Mueller
This paper proposes an adaptive near-hover position controller for quadcopters, which can be deployed to quadcopters of very different mass, size and motor constants, and also shows rapid adaptation to unknown disturbances during runtime.
no code implementations • 4 Aug 2022 • Ashish Kumar, Vasundhra Dahiya, Aditi Sharan
In the case of ABSA, aspect position plays a vital role.
no code implementations • 2 Aug 2022 • Ashish Kumar, R. K. Agrawal, Leve Joseph
Despite the success of Deep Learning-based models in this segmentation task, most of them are heavily parametrized and thus have limited use in practical applications.
no code implementations • 29 Jul 2022 • Ayush Kumar, Ashish Kumar, Aakanksha Prasad, Michael Burch, Shenghui Cheng, Klaus Mueller
We illustrate the usefulness of our tool by applying it to the eye movements of 216 programmers of multiple expertise levels that were collected during two code comprehension tasks.
no code implementations • 30 May 2022 • Ashish Kumar, Zhongyu Li, Jun Zeng, Deepak Pathak, Koushil Sreenath, Jitendra Malik
In this work, we leverage recent advances in rapid adaptation for locomotion control, and extend them to work on bipedal robots.
1 code implementation • 13 Feb 2022 • Saeid Tizpaz-Niari, Ashish Kumar, Gang Tan, Ashutosh Trivedi
This paper investigates the parameter space of machine learning (ML) algorithms in aggravating or mitigating fairness bugs.
no code implementations • CVPR 2022 • Zipeng Fu, Ashish Kumar, Ananye Agarwal, Haozhi Qi, Jitendra Malik, Deepak Pathak
A safety advisor module adds sensed unexpected obstacles to the occupancy map and environment-determined speed limits to the velocity command generator.
no code implementations • 3 Dec 2021 • Naveed A. Abbasi, Jorge Gomez-Ponce, Revanth Kondaveti, Ashish Kumar, Eshan Bhagat, Rakesh N S Rao, Shadi Abu-Surra, Gary Xu, Charlie Zhang, Andreas F. Molisch
The THz band (0. 1-10 THz) has attracted considerable attention for next-generation wireless communications, due to the large amount of available bandwidth that may be key to meet the rapidly increasing data rate requirements.
no code implementations • 30 Nov 2021 • Ashish Kumar, Abeer Alsadoon, P. W. C. Prasad, Salma Abdullah, Tarik A. Rashid, Duong Thu Hang Pham, Tran Quoc Vinh Nguyen
It seems that the proposed system concentrates on minimizing the root mean square error and processing time and improving the direction prediction accuracy, and provides a better result in the accuracy of the stock index.
no code implementations • 25 Oct 2021 • Zipeng Fu, Ashish Kumar, Jitendra Malik, Deepak Pathak
We demonstrate that learning to minimize energy consumption plays a key role in the emergence of natural locomotion gaits at different speeds in real quadruped robots.
no code implementations • 13 Jul 2021 • Ashish Kumar, Laszlo Markus, Norbert Hari
This effect is reflected in the results where the impact of stochastic correlation on calculated CVA is substantial when compared to the case when a high constant correlation is assumed between exposure and credit.
no code implementations • 8 Jul 2021 • Ashish Kumar, Zipeng Fu, Deepak Pathak, Jitendra Malik
Successful real-world deployment of legged robots would require them to adapt in real-time to unseen scenarios like changing terrains, changing payloads, wear and tear.
no code implementations • 28 Apr 2021 • Philippe Raffy, Jean-François Pambrun, Ashish Kumar, David Dubois, Jay Waldron Patti, Robyn Alexandra Cairns, Ryan Young
A CNN-based classifier was developed to identify body regions in CT and MRI.
no code implementations • 16 Jan 2021 • Ashish Kumar, James R. McBride, Gaurav Pandey
We propose an end-to-end real time framework to generate high resolution graphics grade textured 3D map of urban environment.
no code implementations • 16 Jan 2021 • Ashish Kumar, L. Behera
The framework can quickly and incrementally learn novel items in an online manner by real-time data acquisition and generating corresponding ground truths on its own.
no code implementations • 16 Jan 2021 • Ashish Kumar, L. Behera
In the overall process, first, shape histogram of a sample surface (e. g. planar) is computed, which captures the profile of surface normals around a point in form of a probability distribution.
no code implementations • 16 Jan 2021 • Ashish Kumar, Laxmidhar Behera
The primary motivation behind this work is the limitation of the traditional loss functions for unsupervised learning of a given task.
no code implementations • 16 Jan 2021 • Ashish Kumar, Mohit Vohra, Ravi Prakash, L. Behera
In this work, we present a pragmatic approach to enable unmanned aerial vehicle (UAVs) to autonomously perform highly complicated tasks of object pick and place.
1 code implementation • 3 Nov 2020 • Ashish Kumar, Karan Sehgal, Prerna Garg, Vidhya Kamakshi, Narayanan C Krishnan
The current methods to explain the predictions of a pre-trained model rely on gradient information, often resulting in saliency maps that focus on the foreground object as a whole.
no code implementations • 9 Jan 2020 • Siddhartha Vibhu Pharswan, Mohit Vohra, Ashish Kumar, Laxmidhar Behera
In this paper, we present a novel unsupervised learning based algorithm for the selection of feasible grasp regions.
no code implementations • 18 Oct 2019 • Ashish Kumar, Toby Buckley, John B. Lanier, Qiaozhi Wang, Alicia Kavelaars, Ilya Kuzovkin
The challenge that the community sets as a benchmark is usually the challenge that the community eventually solves.
no code implementations • 29 May 2019 • Ashish Kumar, Saurabh Gupta, Jitendra Malik
We demonstrate our proposed approach in context of navigation, and show that we can successfully learn consistent and diverse visuomotor subroutines from passive egocentric videos.
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.
no code implementations • 16 Dec 2018 • Kapil Sharma, Himanshu Ahuja, Ashish Kumar, Nipun Bansal, Gurjit Singh Walia
Extraction of complementary information from the object environment via multiple features and adaption to the target's appearance variations are the key problems of this work.
no code implementations • NeurIPS 2018 • Ashish Kumar, Saurabh Gupta, David Fouhey, Sergey Levine, Jitendra Malik
Equipped with this abstraction, a second network observes the world and decides how to act to retrace the path under noisy actuation and a changing environment.
no code implementations • 11 Jun 2018 • Kapil Sharma, Gurjit Singh Walia, Ashish Kumar, Astitwa Saxena, Kuldeep Singh
Particle Filter(PF) is used extensively for estimation of target Non-linear and Non-gaussian state.
1 code implementation • ICML 2017 • Ashish Kumar, Saurabh Goyal, Manik Varma
This paper develops a novel tree-based algorithm, called Bonsai, for efficient prediction on IoT devices – such as those based on the Arduino Uno board having an 8 bit ATmega328P microcontroller operating at 16 MHz with no native floating point support, 2 KB RAM and 32 KB read-only flash.
1 code implementation • ICML 2017 • Chirag Gupta, Arun Sai Suggala, Ankit Goyal, Harsha Vardhan Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain
Such applications demand prediction models with small storage and computational complexity that do not compromise significantly on accuracy.
no code implementations • 14 Aug 2013 • Sachin Kumar, Ashish Kumar, Pinaki Mitra, Girish Sundaram
For conversion of speech into English text HTK and Julius tools have been used and for conversion of English text query into SQL query we have implemented a System which uses rule based translation to translate English Language Query into SQL Query.