Abhishek Anand
@abhishekanand.bsky.social
quantum phd student at Caltech
Our setting: A learner interacts with a quantum data source over a public eavesdropped channel and wants
• strategy-covertness (hide the learning algorithm) or
• target-covertness (hide the learned object)
We also equip the learner with a private but strictly weaker oracle.
• strategy-covertness (hide the learning algorithm) or
• target-covertness (hide the learned object)
We also equip the learner with a private but strictly weaker oracle.
October 14, 2025 at 11:18 PM
Our setting: A learner interacts with a quantum data source over a public eavesdropped channel and wants
• strategy-covertness (hide the learning algorithm) or
• target-covertness (hide the learned object)
We also equip the learner with a private but strictly weaker oracle.
• strategy-covertness (hide the learning algorithm) or
• target-covertness (hide the learned object)
We also equip the learner with a private but strictly weaker oracle.
Can we reliably learn from untrusted, remote quantum data while keeping our learning strategy and outcomes private? In scirate.com/arxiv/2510.0..., we provide first answers with covert, verifiable quantum learning, extending Canetti–Karchmer ’21 to the quantum setting! 🧵👇
October 14, 2025 at 11:18 PM
Can we reliably learn from untrusted, remote quantum data while keeping our learning strategy and outcomes private? In scirate.com/arxiv/2510.0..., we provide first answers with covert, verifiable quantum learning, extending Canetti–Karchmer ’21 to the quantum setting! 🧵👇